JBoss Rules 5 Reference Guide

JBoss Enterprise BRMS Platform 5

This guide is for developers

Edition 5.3.1

Red Hat Content Services


This guide teaches developers to use JBoss Rules.


Chapter 1. Introduction

1.1. Intended Audience

This book is aimed at system administrators who wish to learn how to utilize the tools in JBoss Rules. It explains how to create new projects, debug projects and how to use editors.

1.2. Aim of the Guide

This guide aims to give users an overview of how to use JBoss Rules. Users will be taken through basic terminologies and learn how to create rules from scratch. There are also a number of tutorials to assist in creating rules for projects.

Chapter 2. Key Terminology

2.1. The Basics

2.1.1. JBoss Rules

JBoss Rules is the name of the business rule engine provided as part of the JBoss Enterprise SOA Platform product.

2.1.2. The JBoss Rules Engine

The JBoss Rules engine is the computer program that applies rules and delivers Knowledge Representation and Reasoning (KRR) functionality to the developer.

2.1.3. Expert Systems

Expert systems are often used to refer to production rules systems or Prolog-like systems. Although acceptable, this comparison is technically incorrect as these are frameworks to build expert systems with, rather than expert systems themselves. An expert system develops once there is a model demonstrating the nature of the expert system itself; that is, a domain encompassing the aspects of an expert system which includes facilities for knowledge acquisition and explanation. Mycin is the most famous expert system.

2.1.4. Production Rules

A production rule is a two-part structure that uses first order logic to represent knowledge. It takes the following form:

2.1.5. The Inference Engine

The inference engine is the part of the JBoss Rules engine which matches production facts and data to rules. It will then perform actions based on what it infers from the information. A production rules system's inference engine is stateful and is responsible for truth maintenance.

2.1.6. Production Memory

The production memory is where rules are stored.

2.1.7. Working Memory

The working memory is the part of the JBoss Rules engine where facts are asserted. From here, the facts can be modified or retracted.

2.1.8. Conflict Resolution Strategy

Conflict resolution is required when there are multiple rules on the agenda. As firing a rule may have side effects on the working memory, the rule engine needs to know in what order the rules should fire (for instance, firing ruleA may cause ruleB to be removed from the agenda).

2.1.9. Hybrid Rule Systems

A hybrid rule system pertains to using both forward-chaining and backward-chaining rule systems to process rules.

2.1.10. Forward-Chaining

Forward-chaining is a production rule system. It is data-driven which means it reacts to the data it is presented. Facts are inserted into the working memory which results in one or more rules being true. They are then placed on the schedule to be executed by the agenda.
JBoss Rules is a forward-chaining engine.

2.1.11. Backward-Chaining

A backward-chaining rule system is goal-driven. This means the system starts with a conclusion which the engine tries to satisfy. If it cannot do so it searches for sub-goals, that is, conclusions that will complete part of the current goal. It continues this process until either the initial conclusion is satisfied or there are no more unsatisfied sub-goals. Prolog is an example of a backward-chaining engine.


Backward-chaining was implemented in JBoss BRMS 5.2.

2.1.12. Reasoning Capabilities

JBoss Rules uses backward-chaining reasoning capabilities to help infer which rules to apply from the data.

2.2. Rete Algorithm

2.2.1. The Rete Root Node

When using Rete00, the root node is where all objects enter the network. From there, it immediately goes to the ObjectTypeNode.

2.2.2. The ObjectTypeNode

The ObjectTypeNode helps to reduce the workload of the rules engine. If there are several objects and the rules engine tried to evaluate every single node against every object, it would waste a lot of cycles. To make things efficient, the ObjectTypeNode is used so the engine only passes objects to the nodes that match the object's type. This way, if an application asserts a new Account, it won't propagate to the nodes for the Order object.
In JBoss Rules, an object which has been asserted will retrieve a list of valid ObjectTypesNodes via a lookup in a HashMap from the object's Class. If this list doesn't exist it scans all the ObjectTypeNodes finding valid matches which it caches in the list. This enables JBoss Rules to match against any Class type that matches with an instanceof check.

2.2.3. AlphaNodes

AlphaNodes are used to evaluate literal conditions. When a rule has multiple literal conditions for a single object type, they are linked together. This means that if an application asserts an Account object, it must first satisfy the first literal condition before it can proceed to the next AlphaNode.
AlphaNodes are propagated using ObjectTypeNodes.

2.2.4. Hashing

JBoss Rules uses hashing to extend Rete by optimizing the propagation from ObjectTypeNode to AlphaNode. Each time an AlphaNode is added to an ObjectTypeNode it adds the literal value as a key to the HashMap with the AlphaNode as the value. When a new instance enters the ObjectType node, rather than propagating to each AlphaNode, it can instead retrieve the correct AlphaNode from the HashMap, thereby avoiding unnecessary literal checks.

2.2.5. BetaNodes

BetaNodes are used to compare two objects and their fields. The objects may be the same or different types.

2.2.6. Alpha Memory

Alpha memory refers to the left input on a BetaNode. In JBoss Rules, this input remembers all incoming objects.

2.2.7. Beta Memory

Beta memory is the term used to refer to the right input of a BetaNode. It remembers all incoming tuples.

2.2.8. Lookups with BetaNodes

When facts enter from one side, you can do a hash lookup returning potentially valid candidates (referred to as indexing). At any point a valid join is found, the Tuple will join with the Object (referred to as a partial match) and then propagate to the next node.

2.2.9. LeftInputNodeAdapters

A LeftInputNodeAdapter takes an Object as an input and propagates a single Object Tuple.

2.2.10. Terminal Nodes

Terminal nodes are used to indicate when a single rule has matched all its conditions (that is, the rule has a full match). A rule with an 'or' conditional disjunctive connective will result in a sub-rule generation for each possible logically branch. Because of this, one rule can have multiple terminal nodes.

2.2.11. Node Sharing

Node sharing is used to prevent unnecessary redundancy. Because many rules repeat the same patterns, node sharing allows users to collapse those patterns so they don't have to be re-evaluated for every single instance.

2.2.12. Node Sharing Example

The following two rules share the first pattern, but not the last:
    vehicle( $car : name == "car" )
    $driver: Driver( typeCar == $sedan )
    System.out.println( $driver.getName() + " drives sedan" );
    Vehicle( $sedan : name == "sedan" )
    $driver : Driver( typeCar != $sedan )
    System.out.println( $driver.getName() + " does not drive sedan" );

2.3. Strong and Loose Coupling

2.3.1. Loose Coupling

Loose coupling involves "loosely" linking rules so that the execution of one rule will not lead to the execution of another.
Generally, a design exhibiting loose coupling is preferable because it allows for more flexibility. If the rules are all strongly coupled, they are likely to be inflexible. More significantly, it indicates that deploying a rule engine is overkill for the situation.

2.3.2. Strong Coupling

Strong coupling is a way of linking rules. If rules are strongly-coupled, it means executing one rule will directly result in the execution of another. In other words, there is a clear chain of logic. (A clear chain can be hard-coded, or implemented using a decision tree.)

2.4. Advantages of a Rule Engine

2.4.1. Declarative Programming

Declarative programming refers to the way the rule engine allows users to declare "what to do" as opposed to "how to do it". The key advantage of this point is that using rules can make it easy to express solutions to difficult problems and consequently have those solutions verified. Rules are much easier to read than code.

2.4.2. Logic and Data Separation

Logic and Data separation refers to the process of de-coupling logic and data components. Using this method, the logic can be spread across many domain objects or controllers and it can all be organized in one or more discrete rules files.

2.4.3. Knowledge Base

A knowledge base is a collection of rules which have been compiled by the KnowledgeBuilder. It is a repository of all the application's knowledge definitions. It may contain rules, processes, functions, and type models. The Knowledge Base itself does not contain instance data (known as facts). Instead, sessions are created from the Knowledge Base into which data can be inserted and where process instances may be started. It is recommended that Knowledge Bases be cached where possible to allow for repeated session creation.

Chapter 3. Quick Start

3.1. Rule Basics

3.1.1. Stateless Knowledge Sessions

A stateless knowledge session is a session without inference. A stateless session can be called like a function in that you can use it to pass data and then receive the result back.
Stateless knowledge sessions are useful in situations requiring validation, calculation, routing and filtering.

3.1.2. Configuring Rules in a Stateless Session

Procedure 3.1. Task

  1. Create a data model like the driver's license example below:
    public class Applicant {
        private String name;
        private int age;
        private boolean valid;
        // getter and setter methods here
  2. Write the first rule. In this example, a rule is added to disqualify any applicant younger than 18:
    package com.company.license
    rule "Is of valid age"
        $a : Applicant( age < 18 )
        $a.setValid( false );
  3. When the Applicant object is inserted into the rule engine, each rule's constraints evaluate it and search for a match. (There is always an implied constraint of "object type" after which there can be any number of explicit field constraints.)
    In the Is of valid age rule there are two constraints:
    • The fact being matched must be of type Applicant
    • The value of Age must be less than eighteen.
    $a is a binding variable. It exists to make possible a reference to the matched object in the rule's consequence (from which place the object's properties can be updated).


    Use of the dollar sign ($) is optional. It helps to differentiate between variable names and field names.


    If the rules are in the same folder as the classes, the classpath resource loader can be used to build the first knowledge base.
  4. Use the KnowledgeBuilder to to compile the list of rules into a knowledge base as shown:
    KnowledgeBuilder kbuilder = KnowledgeBuilderFactory.newKnowledgeBuilder();
    kbuilder.add( ResourceFactory.newClassPathResource( "licenseApplication.drl", 
                  getClass() ), ResourceType.DRL );
    if ( kbuilder.hasErrors() ) {
        System.err.println( kbuilder.getErrors().toString() );
    KnowledgeBase kbase = KnowledgeBaseFactory.newKnowledgeBase();
    kbase.addKnowledgePackages( kbuilder.getKnowledgePackages() );
    The above code snippet looks on the classpath for the licenseApplication.drl file, using the method newClassPathResource(). (The resource type is DRL, short for "Drools Rule Language".)
  5. Check the KnowledgeBuilder for any errors. If there are none, you can build the session.
  6. Execute the data against the rules. (Since the applicant is under the age of eighteen, their application will be marked as "invalid.")
    StatelessKnowledgeSession ksession = kbase.newStatelessKnowledgeSession();
    Applicant applicant = new Applicant( "Mr John Smith", 16 );
    assertTrue( applicant.isValid() );
    ksession.execute( applicant );
    assertFalse( applicant.isValid() );

The preceding code executes the data against the rules. Since the applicant is under the age of 18, the application is marked as invalid.

3.1.3. Configuring Rules with Multiple Objects

Procedure 3.2. Task

  1. To execute rules against any object-implementing iterable (such as a collection), add another class as shown in the example code below:
    public class Applicant {
        private String name;
        private int age;
        // getter and setter methods here
    public class Application {
        private Date dateApplied;
        private boolean valid;
        // getter and setter methods here
  2. In order to check that the application was made within a legitimate time-frame, add this rule:
    package com.company.license
    rule "Is of valid age"
        Applicant( age < 18 )
        $a : Application()     
        $a.setValid( false );
    rule "Application was made this year"
        $a : Application( dateApplied > "01-jan-2009" )     
        $a.setValid( false );
  3. Use the JDK converter to implement the iterable interface. (This method commences with the line Arrays.asList(...).) The code shown below executes rules against an iterable list. Every collection element is inserted before any matched rules are fired:
    StatelessKnowledgeSession ksession = kbase.newStatelessKnowledgeSession();
    Applicant applicant = new Applicant( "Mr John Smith", 16 );
    Application application = new Application();
    assertTrue( application.isValid() );
    ksession.execute( Arrays.asList( new Object[] { application, applicant } ) );
    assertFalse( application.isValid() );


    The execute(Object object) and execute(Iterable objects) methods are actually "wrappers" around a further method called execute(Command command) which comes from the BatchExecutor interface.
  4. Use the CommandFactory to create instructions, so that the following is equivalent to execute( Iterable it ):
    ksession.execute( CommandFactory.newInsertIterable( new Object[] { application, applicant } ) );
  5. Use the BatchExecutor and CommandFactory when working with many different commands or result output identifiers:
    List<Command> cmds = new ArrayList<Command>();
    cmds.add( CommandFactory.newInsert( new Person( "Mr John Smith" ), "mrSmith" );
    cmds.add( CommandFactory.newInsert( new Person( "Mr John Doe" ), "mrDoe" );
    BatchExecutionResults results = ksession.execute( CommandFactory.newBatchExecution( cmds ) );
    assertEquals( new Person( "Mr John Smith" ), results.getValue( "mrSmith" ) );


    CommandFactory supports many other commands that can be used in the BatchExecutor. Some of these are StartProcess, Query and SetGlobal.

3.1.4. Stateful Sessions

A stateful session allow you to make iterative changes to facts over time. As with the StatelessKnowledgeSession, the StatefulKnowledgeSession supports the BatchExecutor interface. The only difference is the FireAllRules command is not automatically called at the end.


Ensure that the dispose() method is called after running a stateful session. This is to ensure that there are no memory leaks. This is due to the fact that knowledge bases will obtain references to stateful knowledge sessions when they are created.

3.1.5. Common Use Cases for Stateful Sessions

For example, you can monitor a stock market and automate the buying process.
Stateful sessions can be used to run fault-finding processes. They could also be used for medical diagnostic processes.
For example, they could be applied to problems involving parcel tracking and delivery provisioning.
Ensuring compliance
For example, to validate the legality of market trades.

3.1.6. Stateful Session Monitoring Example

Procedure 3.3. Task

  1. Create a model of what you want to monitor. In this example involving fire alarms, the rooms in a house have been listed. Each has one sprinkler. A fire can start in any of the rooms:
    public class Room 
    	private String name
    		// getter and setter methods here
    public class Sprinkler 
    	private Room room;
    	private boolean on;
    	// getter and setter methods here
    public class Fire 
    	private Room room;
    	// getter and setter methods here
    public class Alarm 
  2. The rules must express the relationships between multiple objects (to define things such as the presence of a sprinkler in a certain room). To do this, use a binding variable as a constraint in a pattern. This results in a cross-product.
  3. Create an instance of the Fire class and insert it into the session.
    The rule below adds a binding to Fire object's room field to constrain matches. This so that only the sprinkler for that room is checked. When this rule fires and the consequence executes, the sprinkler activates:
    rule "When there is a fire turn on the sprinkler"
        Fire($room : room)
        $sprinkler : Sprinkler( room == $room, on == false )
        modify( $sprinkler ) { setOn( true ) };
        System.out.println("Turn on the sprinkler for room "+$room.getName());
    Whereas the stateless session employed standard Java syntax to modify a field, the rule above uses the modify statement. (It acts much like a "with" statement.)

3.1.7. First Order Logic

First order logic allows you to look at sets of data instead of individual instances.

3.1.8. Configuring Rules with First Order Logic

Procedure 3.4. Task

  1. Configure a pattern featuring the keyword Not. First order logic ensures rules will only be matched when no other keywords are present. In this example, the rule turns the sprinkler off when the fire is extinguished:
    rule "When the fire is gone turn off the sprinkler"
        $room : Room( )
        $sprinkler : Sprinkler( room == $room, on == true )
        not Fire( room == $room )
        modify( $sprinkler ) { setOn( false ) };
        System.out.println("Turn off the sprinkler for room "+$room.getName());
  2. An Alarm object is created when there is a fire, but only one Alarm is needed for the entire building no matter how many fires there might be. Not's complement, exists can now be introduced. It matches one or more instances of a category:
    rule "Raise the alarm when we have one or more fires"
        exists Fire()
        insert( new Alarm() );
        System.out.println( "Raise the alarm" );
  3. If there are no more fires, the alarm must be deactivated. To turn it off, use Not again:
    rule "Cancel the alarm when all the fires have gone"
        not Fire()
        $alarm : Alarm()
        retract( $alarm );
        System.out.println( "Cancel the alarm" );
  4. Use this code to print a general health status message when the application first starts and also when the alarm and all of the sprinklers have been deactivated:
    rule "Status output when things are ok"
        not Alarm()
        not Sprinkler( on == true ) 
        System.out.println( "Everything is ok" );
  5. Store the rules in a file called fireAlarm.drl. Save this file in a sub-directory on the class-path.
  6. Finally, build a knowledge base, using the new name, fireAlarm.drl:
    KnowledgeBuilder kbuilder = KnowledgeBuilderFactory.newKnowledgeBuilder();
    kbuilder.add( ResourceFactory.newClassPathResource( "fireAlarm.drl", 
    										getClass() ), ResourceType.DRL );
    if ( kbuilder.hasErrors() )
    	System.err.println( kbuilder.getErrors().toString() );
    StatefulKnowledgeSession ksession = kbase.newStatefulKnowledgeSession();

3.1.9. Rule System Sample Configuration

Procedure 3.5. Task

  1. Insert ksession.fireAllRules(). This grants the matched rules permission to run but, since there is no fire in this example, they will merely produce the health message:
    String[] names = new String[]{"kitchen","bedroom","office","livingroom"};
    Map<String,Room> name2room = new HashMap<String,Room>();
    for( String name: names )
    	Room room = new Room( name );
    	name2room.put( name, room );
    	ksession.insert( room );
    	Sprinkler sprinkler = new Sprinkler( room );
    	ksession.insert( sprinkler );
    The resulting message reads:
    > Everything is okay
  2. Create and insert two fires. (A fact handle will be kept.)
  3. With the fires now in the engine, call fireAllRules(). The alarm will be raised and the respective sprinklers will be turned on:
    Fire kitchenFire = new Fire( name2room.get( "kitchen" ) );
    Fire officeFire = new Fire( name2room.get( "office" ) );
    FactHandle kitchenFireHandle = ksession.insert( kitchenFire );
    FactHandle officeFireHandle = ksession.insert( officeFire );
    The resulting message reads:
    > Raise the alarm
    > Turn on the sprinkler for room kitchen
    > Turn on the sprinkler for room office
  4. When the fires are extinguished, the fire objects are retracted and the sprinklers are turned off. At this point in time, the alarm is canceled and the health message displays once more:
    ksession.retract( kitchenFireHandle );
    ksession.retract( officeFireHandle );
    The resulting message reads:
    > Turn off the sprinkler for room office
    > Turn off the sprinkler for room kitchen
    > Cancel the alarm
    > Everything is okay       

3.2. JBoss Rules Theory

3.2.1. Methods in JBoss Rules

Methods are different to rules. They are called directly and are used to pass specific instances. A single call results in a single execution.

3.2.2. Method Example

A method looks like this:
public void helloWorld(Person person) {
    if ( person.getName().equals( "Chuck" ) ) {
        System.out.println( "Hello Chuck" );

3.2.3. Rule Example

A rule looks like this:
rule "Hello World"
        Person( name == "Chuck" )
        System.out.println( "Hello Chuck" );

3.2.4. Cross-Products

When two or more sets of data are combined, the result is called a cross-product.

3.2.5. Cross-Product Constraining

Procedure 3.6. Task

  • To prevent a rule from outputting a huge amount of cross-products, you should constrain the cross-products themselves. Do this using the variable constraint seen below:
        $room : Room()
        $sprinkler : Sprinkler( room == $room )
        System.out.println( "room:" + $room.getName() +
                            " sprinkler:" + $sprinkler.getRoom().getName() );
    The following output will be displayed:
    room:office sprinkler:office
    room:kitchen sprinkler:kitchen
    room:livingroom sprinkler:livingroom
    room:bedroom sprinkler:bedroom

Only four rows are outputted with the correct sprinkler for each room. Without this variable, every row in the Room table would have been joined with every row in the Sprinkler table resulting in many lines of output.

3.2.6. The Inference Engine

The inference engine is the part of the JBoss Rules engine which matches production facts and data to rules. It will then perform actions based on what it infers from the information. A production rules system's inference engine is stateful and is responsible for truth maintenance.

3.2.7. Inference Example

In this example, a Person fact with an age field and a rule that provides age policy control is used. Inference is used to determine if a Person is an adult or a minor, then act on the result:
rule "Infer Adult"
  $p : Person( age >= 18 )
  insert( new IsAdult( $p ) )
In the above snippet, every Person who is 18 or over will have an instance of IsAdult inserted for them. This fact is special in that it is known as a relation. We can use this inferred relation in any rule:
$p : Person()
IsAdult( person == $p )

3.3. Advanced Concepts and Theory

3.3.1. Logical Assertions

After a standard object insertion, you have to retract facts explicitly. With logical assertions, the fact that was asserted will be automatically retracted when the conditions that asserted it in the first place are no longer true. It will be retracted only if there isn't any single condition that supports the logical assertion.

3.3.2. Stated Insertions

Normal insertions are said to be stated, as in "stating a fact". Using a HashMap and a counter, you can track how many times a particular equality is stated. This means you can count how many different instances are equal.

3.3.3. Justified Insertions

When an object is logically inserted, it is said to be justified. It is considered to be justified by the firing rule. For each logical insertion there can only be one equal object, and each subsequent equal logical insertion increases the justification counter for this logical assertion. A justification is removed when the creating rule's LHS becomes untrue, and the counter is decreased accordingly. As soon as there are no more justifications, the logical object is automatically retracted.


If you try to logically insert an object when there is an equal stated object, this will fail and return null. If you state an object that has an existing equal object that is justified, you will override the Fact. How this override works depends on the configuration setting WM_BEHAVIOR_PRESERVE. When the property is set to discard, you can use the existing handle and replace the existing instance with the new Object, which is the default behavior. Otherwise you should override it to stated but create an new FactHandle.

3.3.5. Stated Insertion Flowchart

3.3.6. Logical Insertion Flowchart

3.3.7. The Truth Maintenance System

The JBoss Rules Truth Maintenance System (TMS) is a method of representing beliefs and their related dependencies/justifications in a knowledge base.


For Truth Maintenance (and logical assertions) to work, the Fact objects must override equals and hashCode methods correctly. As the truth maintenance system needs to know when two different physical objects are equal in value, both equals and hashCode must be overridden correctly, as per the Java standard.
Two objects are equal only if their equals methods return true for each other and if their hashCode methods return the same values. You must override both equals and hashCode.

3.3.8. The insertLogical Fact

The insertLogical fact is part of the JBoss Rules TMS. It "inserts logic" so that rules behave and are modified according to the situation. For example, the insertLogical fact can be added to a set of rules so that when a rule becomes false, the fact is automatically retracted.

3.3.9. Using Inference and TMS

Procedure 3.7. Task

  1. In this example we will use a bus pass issuing system. See the code snippet below:
    rule "Issue Child Bus Pass" when
      $p : Person( age < 16 )
      insert(new ChildBusPass( $p ) );
    rule "Issue Adult Bus Pass" when
      $p : Person( age >= 16 )
      insert(new AdultBusPass( $p ) );
  2. Insert the insertLogical property to provide inference:
    rule "Infer Child" when
        $p : Person( age < 16 )
        insertLogical( new IsChild( $p ) )
    rule "Infer Adult" when
        $p : Person( age >= 16 )
        insertLogical( new IsAdult( $p ) )
  3. Re-enter the code to issue the passes. These two configurations can also be logically inserted, as the TMS supports chaining of logical insertions for a cascading set of retracts:
    rule "Issue Child Bus Pass" when
      $p : Person( )
           IsChild( person == $p )
        insertLogical(new ChildBusPass( $p ) );
    rule "Issue Adult Bus Pass" when
      $p : Person( age >= 16 )
           IsAdult( person =$p )
        insertLogical(new AdultBusPass( $p ) );
    Now when the person changes from being 15 to 16, both the IsChild fact and the person's ChildBusPass fact are automatically retracted.
  4. Optionally, insert the not conditional element to handle notifications. (In this example, a request for the returning of the pass.) When the TMS automatically retracts the ChildBusPass object, this rule triggers and sends a request to the person:
    rule "Return ChildBusPass Request "when
      $p : Person( )
           not( ChildBusPass( person == $p ) )
        requestChildBusPass( $p );

Chapter 4. Processing

4.1. Agenda

The Agenda is a Rete feature. During actions on the WorkingMemory, rules may become fully matched and eligible for execution. A single Working Memory Action can result in multiple eligible rules. When a rule is fully matched an Activation is created, referencing the rule and the matched facts, and placed onto the Agenda. The Agenda controls the execution order of these Activations using a Conflict Resolution strategy.

4.2. Agenda Processing

The engine cycles repeatedly through two phases:
  1. Working Memory Actions. This is where most of the work takes place, either in the Consequence (the RHS itself) or the main Java application process. Once the Consequence has finished or the main Java application process calls fireAllRules() the engine switches to the Agenda Evaluation phase.
  2. Agenda Evaluation. This attempts to select a rule to fire. If no rule is found it exits, otherwise it fires the found rule, switching the phase back to Working Memory Actions.
The process repeats until the agenda is clear, in which case control returns to the calling application. When Working Memory Actions are taking place, no rules are being fired.

4.3. Default Conflict Resolution Strategies

Salience (Priority)
A user can specify that a certain rule has a higher priority (by giving it a higher number) than other rules. In that case, the rule with higher salience will be preferred.
LIFO (last in, first out)
LIFO priorities are based on the assigned Working Memory Action counter value, with all rules created during the same action receiving the same value. The execution order of a set of firings with the same priority value is arbitrary.


As a general rule, it is a good idea not to count on rules firing in any particular order, and to author the rules without worrying about a "flow". However when a flow is needed a number of possibilities exist, including but not limited to: agenda groups, rule flow groups, activation groups, control/semaphore facts. These are discussed in later sections.

4.4. AgendaGroup

Agenda groups are a way to partition rules on the agenda. At any one time, only one group has "focus" which means that activations for rules in that group only will take effect. You can also have rules with "auto focus" which means that the focus is taken for its agenda group when that rule's conditions are true.
Agenda groups are known as "modules" in CLIPS terminology. Agenda groups provide a way to create a "flow" between grouped rules. You can switch the group which has focus either from within the rule engine, or via the API. If your rules have a clear need for multiple "phases" or "sequences" of processing, consider using agenda-groups for this purpose.

4.5. setFocus()

Each time setFocus() is called it pushes the specified Agenda Group onto a stack. When the focus group is empty it is popped from the stack and the focus group that is now on top evaluates. An Agenda Group can appear in multiple locations on the stack. The default Agenda Group is "MAIN", with all rules which do not specify an Agenda Group being in this group. It is also always the first group on the stack, given focus initially, by default.

4.6. setFocus() Example

This is what the setFocus() element looks like:
ksession.getAgenda().getAgendaGroup( "Group A" ).setFocus();

4.7. ActivationGroup

An activation group is a set of rules bound together by the same "activation-group" rule attribute. In this group only one rule can fire, and after that rule has fired all the other rules are cancelled from the agenda. The clear() method can be called at any time, which cancels all of the activations before one has had a chance to fire.

4.8. ActivationGroup Example

This is what an ActivationGroup looks like:
ksession.getAgenda().getActivationGroup( "Group B" ).clear();

4.9. RuleFlowGroup

A rule flow group is a group of rules associated by the "ruleflow-group" rule attribute. These rules can only fire when the group is activate. The group itself can only become active when the elaboration of the ruleflow diagram reaches the node representing the group. Here too, the clear() method can be called at any time to cancels all activations still remaining on the Agenda.

4.10. RuleFlowGroup Example

This is what the RuleFlowGroup property looks like:
ksession.getAgenda().getRuleFlowGroup( "Group C" ).clear();

4.11. The Difference Between Rules and Methods

  • Methods are called directly.
  • Specific instances are passed.
  • One call results in a single execution.
  • Rules execute by matching against any data as long it is inserted into the engine.
  • Rules can never be called directly.
  • Specific instances cannot be passed to a rule.
  • Depending on the matches, a rule may fire once or several times, or not at all.

4.12. Cross Product Example

Below, a rule consisting of an unconstrained fire alarm situation is shown:
    $room : Room()
    $sprinkler : Sprinkler()
    System.out.println( "room:" + $room.getName() +
                        " sprinkler:" + $sprinkler.getRoom().getName() );
In SQL terms this would be like doing select * from Room, Sprinkler and every row in the Room table would be joined with every row in the Sprinkler table resulting in the following output:
room:office sprinkler:office
room:office sprinkler:kitchen
room:office sprinkler:livingroom
room:office sprinkler:bedroom
room:kitchen sprinkler:office
room:kitchen sprinkler:kitchen
room:kitchen sprinkler:livingroom
room:kitchen sprinkler:bedroom
room:livingroom sprinkler:office
room:livingroom sprinkler:kitchen
room:livingroom sprinkler:livingroom
room:livingroom sprinkler:bedroom
room:bedroom sprinkler:office
room:bedroom sprinkler:kitchen
room:bedroom sprinkler:livingroom
room:bedroom sprinkler:bedroom
These cross products can become huge and can contain spurious data. This can be averted by constraining the cross products, which is done with the variable constraint:
    $room : Room()
    $sprinkler : Sprinkler( room == $room )
    System.out.println( "room:" + $room.getName() +
                        " sprinkler:" + $sprinkler.getRoom().getName() );
This results in just four rows of data, with the correct Sprinkler for each Room. In SQL (actually HQL) the corresponding query would be select * from Room, Sprinkler where Room == Sprinkler.room.
room:office sprinkler:office
room:kitchen sprinkler:kitchen
room:livingroom sprinkler:livingroom
room:bedroom sprinkler:bedroom

4.13. Activations, Agenda and Conflict Sets Example

In this example, a cashflow calculation system is featured. These are the three classes implemented:
public class CashFlow {
    private Date   date;
    private double amount;
    private int    type;
    long           accountNo;
    // getter and setter methods here

public class Account {
    private long   accountNo;
    private double balance;
    // getter and setter methods here

public AccountPeriod {
    private Date start;
    private Date end;
    // getter and setter methods here
Two rules can be used to determine the debit and credit for that quarter and update the Account balance. The two rules below constrain the cashflows for an account for a given time period. Notice the "&&" which use short cut syntax to avoid repeating the field name twice.
rule "increase balance for credits"
  ap : AccountPeriod()
  acc : Account( $accountNo : accountNo )
  CashFlow( type == CREDIT,
            accountNo == $accountNo,
            date >= ap.start && <= ap.end,
            $amount : amount )
  acc.balance  += $amount;
rule "decrease balance for debits" 
  ap : AccountPeriod() 
  acc : Account( $accountNo : accountNo ) 
  CashFlow( type == DEBIT, 
            accountNo == $accountNo,
            date >= ap.start && <= ap.end, 
            $amount : amount ) 
  acc.balance -= $amount; 
If the AccountPeriod is set to the first quarter we constrain the rule "increase balance for credits" to fire on two rows of data and "decrease balance for debits" to act on one row of data.
The data is matched during the insertion stage and only fires after fireAllRules() is called. Meanwhile, the rule plus its matched data is placed on the Agenda and referred to as an Activation. The Agenda is a table of Activations that are able to fire and have their consequences executed, as soon as fireAllRules() is called. Activations on the Agenda are executed in turn. Notice that the order of execution so far is considered arbitrary.
After all of the above activations are fired, the account has a balance of -25.
If the AccountPeriod is updated to the second quarter, we have just a single matched row of data, and thus just a single Activation on the Agenda.
The firing of that Activation results in a balance of 25.

4.14. Conflict Resolver Strategy

When there is one or more Activations on the Agenda they are said to be in conflict, and a conflict resolver strategy is used to determine the order of execution. At the simplest level the default strategy uses salience to determine rule priority.

4.15. Conflict Resolver Strategy Example

Each rule has a default value of 0, the higher the value the higher the priority. To illustrate this, a rule is added to print the account balance. The goal is for the rule to be executed after all the debits and credits have been applied for all accounts. This is done by assigning a negative salience to this rule so that it fires after all rules with the default salience 0.
rule "Print balance for AccountPeriod"
        salience -50
        ap : AccountPeriod()
        acc : Account()        
        System.out.println( acc.accountNo + " : " + acc.balance );    

4.16. Trigger Example

Table 4.1. Trigger Example

Rule View View Trigger
select * from Account acc,
              Cashflow cf,
              AccountPeriod ap      
where acc.accountNo == cf.accountNo and 
      cf.type == CREDIT and
      cf.date >= ap.start and 
      cf.date <= ap.end
select * from Account acc, 
              Cashflow cf,
              AccountPeriod ap 
where acc.accountNo == cf.accountNo and 
      cf.type == DEBIT and
      cf.date >= ap.start and 
      cf.date <= ap.end
trigger : acc.balance += cf.amount
trigger : acc.balance -= cf.amount

4.17. ruleflow-group Example

The use of the ruleflow-group attribute in a rule is shown below:
rule "increase balance for credits"
  ruleflow-group "calculation"
  ap : AccountPeriod()
  acc : Account( $accountNo : accountNo )
  CashFlow( type == CREDIT,
            accountNo == $accountNo,
            date >= ap.start && <= ap.end,
            $amount : amount )
  acc.balance  += $amount;
rule "Print balance for AccountPeriod"
  ruleflow-group "report"
  ap : AccountPeriod()
  acc : Account()
  System.out.println( acc.accountNo +
                      " : " + acc.balance );    

4.18. Inference Example

In the example below, the IsAdult property is used to infer a person's age.
rule "Infer Adult"
  $p : Person( age >= 18 )
  insert( new IsAdult( $p ) )
This inferred relation can be used in any rule:
$p : Person()
IsAdult( person == $p )
Further, de-coupling the knowledge process decreases the chance of data leakage and third party modifications to the information.

4.19. Implementing Inference and TruthMaintenance

Procedure 4.1. Task

  1. Open a set of rules. In this example, a buss pass issuing system will be used:
    rule "Issue Child Bus Pass" when
      $p : Person( age < 16 )
      insert(new ChildBusPass( $p ) );
    rule "Issue Adult Bus Pass" when
      $p : Person( age >= 16 )
      insert(new AdultBusPass( $p ) );
  2. Insert the fact insertLogical and add the terms you wish to be inferred.
    rule "Infer Child" when
      $p : Person( age < 16 )
        insertLogical( new IsChild( $p ) )
    rule "Infer Adult" when
        $p : Person( age >= 16 )
        insertLogical( new IsAdult( $p ) )
    The fact has been logically inserted. This fact is dependent on the truth of the "when" clause. It means that when the rule becomes false the fact is automatically retracted. This works particularly well as the two rules are mutually exclusive. In the above rules, the IsChild fact is inserted if the child is under 16. It is then automatically retracted if the person is over 16 and the IsAdult fact is inserted.
  3. Insert the code to issue the passes. These can also be logically inserted as the TMS supports chaining of logical insertions for a cascading set of retracts.
    rule "Issue Child Bus Pass" when
        $p : Person( )
        IsChild( person == $p )
        insertLogical(new ChildBusPass( $p ) );
    rule "Issue Adult Bus Pass" when
        $p : Person( age >= 16 )
        IsAdult( person =$p )
        insertLogical(new AdultBusPass( $p ) );
    Now when the person changes from being 15 to 16, not only is the IsChild fact automatically retracted, so is the person's ChildBusPass fact.
  4. Insert the 'not' conditional element to handle notifications. (In this situation, a request for the returning of the pass.) When the TMS automatically retracts the ChildBusPass object, this rule triggers and sends a request to the person:
    rule "Return ChildBusPass Request "when
      $p : Person( )
           not( ChildBusPass( person == $p ) )
        requestChildBusPass( $p );

Chapter 5. The Rule Language

5.1. Rule Language

5.1.1. Overview

Drools has a native rule language. This format is very light in terms of punctuation, and supports natural and domain specific languages via "expanders" that allow the language to morph to your problem domain.

5.1.2. A rule file

A rule file is typically a file with a .drl extension. In a DRL file you can have multiple rules, queries and functions, as well as some resource declarations like imports, globals, and attributes that are assigned and used by your rules and queries. However, you are also able to spread your rules across multiple rule files (in that case, the extension .rule is suggested, but not required) - spreading rules across files can help with managing large numbers of rules. A DRL file is simply a text file.

5.1.3. The structure of a rule file

The overall structure of a rule file is the following:

Example 5.1. Rules file

package package-name





The order in which the elements are declared is not important, except for the package name that, if declared, must be the first element in the rules file. All elements are optional, so you will use only those you need.

5.1.4. What is a rule

For the inpatients, just as an early view, a rule has the following rough structure:
rule "name"
Mostly punctuation is not needed, even the double quotes for "name" are optional, as are newlines. Attributes are simple (always optional) hints to how the rule should behave. LHS is the conditional parts of the rule, which follows a certain syntax which is covered below. RHS is basically a block that allows dialect specific semantic code to be executed.
It is important to note that white space is not important, except in the case of domain specific languages, where lines are processed one by one and spaces may be significant to the domain language.

5.1.5. Hard Keywords

Hard keywords are words which you cannot use when naming your domain objects, properties, methods, functions and other elements that are used in the rule text. The hard keywords are true, false, and null.

5.1.6. Soft Keywords

Soft keywords can be used for naming domain objects, properties, methods, functions and other elements. The rules engine recognizes their context and processes them accordingly.

5.1.7. List of Soft Keywords

  • lock-on-active
  • date-effective
  • date-expires
  • no-loop
  • auto-focus
  • activation-group
  • agenda-group
  • ruleflow-group
  • entry-point
  • duration
  • package
  • import
  • dialect
  • salience
  • enabled
  • attributes
  • rule
  • extend
  • when
  • then
  • template
  • query
  • declare
  • function
  • global
  • eval
  • not
  • in
  • or
  • and
  • exists
  • forall
  • accumulate
  • collect
  • from
  • action
  • reverse
  • result
  • end
  • over
  • init


Comments are sections of text that are ignored by the rule engine. They are stripped out when they are encountered, except inside semantic code blocks (like a rule's RHS).

5.1.9. Single Line Comment Example

This is what a single line comment looks like. To create single line comments, you can use '//'. The parser will ignore anything in the line after the comment symbol:
rule "Testing Comments"
    // this is a single line comment
    eval( true ) // this is a comment in the same line of a pattern
    // this is a comment inside a semantic code block

5.1.10. Multi-Line Comment Example

This is what a multi-line comment looks like. This configuration comments out blocks of text, both in and outside semantic code blocks:
rule "Test Multi-line Comments"
    /* this is a multi-line comment
       in the left hand side of a rule */
    eval( true )
    /* and this is a multi-line comment
       in the right hand side of a rule */

5.1.11. Error Messages

JBoss Rules introduces standardized error messages. This standardization aims to help users to find and resolve problems in a easier and faster way.

5.1.12. Error Message Format

This is the standard error message format.
Error Message Format Example

Figure 5.1. Error Message Format Example

1st Block: This area identifies the error code.
2nd Block: Line and column information.
3rd Block: Some text describing the problem.
4th Block: This is the first context. Usually indicates the rule, function, template or query where the error occurred. This block is not mandatory.
5th Block: Identifies the pattern where the error occurred. This block is not mandatory.

5.1.13. Error Messages Description

Table 5.1. Error Messages

Error Message Description Example  
[ERR 101] Line 4:4 no viable alternative at input 'exits' in rule one
Indicates when the parser came to a decision point but couldn't identify an alternative.
1: rule one
2:   when
3:     exists Foo()
4:     exits Bar()
5:   then
6: end
[ERR 101] Line 3:2 no viable alternative at input 'WHEN'
This message means the parser has encountered the token WHEN (a hard keyword) which is in the wrong place, since the rule name is missing.
1: package org.drools;
2: rule
3:   when
4:     Object()
5:   then
6:     System.out.println("A RHS");
7: end
[ERR 101] Line 0:-1 no viable alternative at input '<eof>' in rule simple_rule in pattern [name]
Indicates an open quote, apostrophe or parentheses.
1: rule simple_rule
2:   when
3:     Student( name == "Andy )
4:   then
5: end
[ERR 102] Line 0:-1 mismatched input '<eof>' expecting ')' in rule simple_rule in pattern Bar
Indicates that the parser was looking for a particular symbol that it didn't end at the current input position.
1: rule simple_rule
2:   when
3:     foo3 : Bar(
[ERR 102] Line 0:-1 mismatched input '<eof>' expecting ')' in rule simple_rule in pattern [name]
This error is the result of an incomplete rule statement. Usually when you get a 0:-1 position, it means that parser reached the end of source. To fix this problem, it is necessary to complete the rule statement.
1: package org.drools;
3: rule "Avoid NPE on wrong syntax"
4:   when
5:     not( Cheese( ( type == "stilton", price == 10 ) || ( type == "brie", price == 15 ) ) from $cheeseList )
6:   then
7:     System.out.println("OK");
8: end
[ERR 103] Line 7:0 rule 'rule_key' failed predicate: {(validateIdentifierKey(DroolsSoftKeywords.RULE))}? in rule
A validating semantic predicate evaluated to false. Usually these semantic predicates are used to identify soft keywords.
1: package nesting;
 2: dialect "mvel"
 4: import org.drools.Person
 5: import org.drools.Address
 7: fdsfdsfds
 9: rule "test something"
10:   when
11:     p: Person( name=="Michael" )
12:   then
13:     p.name = "other";
14:     System.out.println(p.name);
15: end
[ERR 104] Line 3:4 trailing semi-colon not allowed in rule simple_rule
This error is associated with the eval clause, where its expression may not be terminated with a semicolon. This problem is simple to fix: just remove the semi-colon.
1: rule simple_rule
2:   when
3:     eval(abc();)
4:   then
5: end
[ERR 105] Line 2:2 required (...)+ loop did not match anything at input 'aa' in template test_error
The recognizer came to a subrule in the grammar that must match an alternative at least once, but the subrule did not match anything. To fix this problem it is necessary to remove the numeric value as it is neither a valid data type which might begin a new template slot nor a possible start for any other rule file construct.
1: template test_error
2:   aa s  11;
3: end

5.1.14. Package

A package is a collection of rules and other related constructs, such as imports and globals. The package members are typically related to each other, such as HR rules. A package represents a namespace, which ideally is kept unique for a given grouping of rules. The package name itself is the namespace, and is not related to files or folders in any way.
It is possible to assemble rules from multiple rule sources, and have one top level package configuration that all the rules are kept under (when the rules are assembled). It is not possible to merge into the same package resources declared under different names. A single Rulebase may, however, contain multiple packages built on it. A common structure is to have all the rules for a package in the same file as the package declaration (so that is it entirely self-contained).

5.1.15. Import Statements

Import statements work like import statements in Java. You need to specify the fully qualified paths and type names for any objects you want to use in the rules. JBoss Rules automatically imports classes from the Java package of the same name, and also from the package java.lang.

5.1.16. Using Globals

In order to use globals you must:
  1. Declare the global variable in the rules file and use it in rules. Example:
    global java.util.List myGlobalList;
    rule "Using a global"
        eval( true )
        myGlobalList.add( "Hello World" );
  2. Set the global value on the working memory. It is best practice to set all global values before asserting any fact to the working memory. Example:
    List list = new ArrayList();
    WorkingMemory wm = rulebase.newStatefulSession();
    wm.setGlobal( "myGlobalList", list );

5.1.17. The From Element

The from element allows you to pass a Hibernate session as a global. It also lets you pull data from a named Hibernate query.

5.1.18. Using Globals with an e-Mail Service

Procedure 5.1. Task

  1. Open the integration code that is calling the rule engine.
  2. Obtain your emailService object and then set it in the working memory.
  3. In the DRL, declare that you have a global of type emailService and give it the name "email".
  4. In your rule consequences, you can use things like email.sendSMS(number, message).


    Globals are not designed to share data between rules and they should never be used for that purpose. Rules always reason and react to the working memory state, so if you want to pass data from rule to rule, assert the data as facts into the working memory.


    Do not set or change a global value from inside the rules. We recommend to you always set the value from your application using the working memory interface.

5.2. KnowledgeBuilder

5.2.1. The KnowledgeBuilder

The KnowledgeBuilder is responsible for taking source files, such as a DRL file or an Excel file, and turning them into a Knowledge Package of rule and process definitions which a Knowledge Base can consume. An object of the class ResourceType indicates the type of resource the builder is being asked to process.
A screen shot of the org.drools.builder chart.

Figure 5.2. Builder Chart

5.2.2. The ResourceFactory

The ResourceFactory provides capabilities to load resources from a number of sources: java.io.Reader, the classpath, a URL, a java.io.File, or a byte array. Binary files, such as decision tables (Excel's .xls files), should not be passed in with Reader, which is only suitable for text based resources.
A chart of the org.drools.builder.

Figure 5.3. KnowledgeBuilder Chart

5.2.3. Creating a new KnowledgeBuilder

Procedure 5.2. Task

  1. Open the KnowledgeBuilderFactory.
  2. Create a new default configuration.
  3. Enter this into the configuration:
    KnowledgeBuilder kbuilder = KnowledgeBuilderFactory.newKnowledgeBuilder();
    The first parameter is for properties and is optional. If left blank, the default options will be used. The options parameter can be used for things like changing the dialect or registering new accumulator functions.
  4. To add a KnowledgeBuilder with a custom ClassLoader, use this code:
    KnowledgeBuilderConfiguration kbuilderConf = KnowledgeBuilderFactory.newKnowledgeBuilderConfiguration(null, classLoader );
    KnowledgeBuilder kbuilder = KnowledgeBuilderFactory.newKnowledgeBuilder(kbuilderConf);

5.2.4. Adding DRL Resources

Procedure 5.3. Task

  1. Resources of any type can be added iteratively. Below, a DRL file is added. The Knowledge Builder can handle multiple namespaces, so you can combine resources regardless of their namespace:
    kbuilder.add( ResourceFactory.newFileResource( "/project/myrules.drl" ),
  2. Check the compilation results after each resource addition. The KnowledgeBuilder can report compilation results of 3 different severities: ERROR, WARNING and INFO.
    • An ERROR indicates that the compilation of the resource failed. You should not add more resources or retrieve the Knowledge Packages if there are errors. getKnowledgePackages() returns an empty list if there are errors.
    • WARNING and INFO results can be ignored, but are available for inspection nonetheless.

5.2.5. KnowledgeBuilder Result Inspection Methods

The KnowledgeBuilder API offers several methods to check and retrieve the build results for a list of severities:
     * Return the knowledge builder results for the listed severities.
     * @param severities
     * @return
    KnowledgeBuilderResults getResults(ResultSeverity... severities);
     * Checks if the builder generated any results of the listed severities
     * @param severities
     * @return
    boolean hasResults(ResultSeverity... severities ;
The KnowledgeBuilder API also has two helper methods to inspect for errors: hasErrors() and getErrors():
if( kbuilder.hasErrors() ) {
    System.out.println( kbuilder.getErrors() );

5.2.6. Getting the KnowledgePackages

When all the resources have been added and there are no errors, the collection of Knowledge Packages can be retrieved. It is a java.util.Collection because there is one KnowledgePackage per package namespace. These Knowledge Packages are serializable and often used as a unit of deployment.
The Knowledge Package can been seen below:
Collection<KnowledgePackage> kpkgs = kbuilder.getKnowledgePackages();

5.2.7. Extended KnowledgeBuilder Example

This is what a complete KnowledgeBuilder package looks like:
KnowledgeBuilder kbuilder = KnowledgeBuilderFactory.newKnowledgeBuilder();
if( kbuilder.hasErrors() ) {
    System.out.println( kbuilder.getErrors() );

KnowledgeBuilder kbuilder = KnowledgeBuilderFactory.newKnowledgeBuilder();
kbuilder.add( ResourceFactory.newFileResource( "/project/myrules1.drl" ),
kbuilder.add( ResourceFactory.newFileResource( "/project/myrules2.drl" ),

if( kbuilder.hasErrors() ) {
    System.out.println( kbuilder.getErrors() );

Collection<KnowledgePackage> kpkgs = kbuilder.getKnowledgePackages();

5.2.8. Using KnowledgeBuilder in Batch Mode

The KnowledgeBuilder has a batch mode with a fluent interface. It allows you to build multiple DRLs at once as in the following example:
KnowledgeBuilder kbuilder = KnowledgeBuilderFactory.newKnowledgeBuilder();
        .add( ResourceFactory.newFileResource( "/project/myrules1.drl" ), ResourceType.DRL )
        .add( ResourceFactory.newFileResource( "/project/myrules2.drl" ), ResourceType.DRL )
        .add( ResourceFactory.newFileResource( "/project/mytypes1.drl" ), ResourceType.DRL )

5.2.9. Discard the Build of the Last Added DRL

The KnowledgeBuilder (regardless if you are using the batch mode or not) also allows you to discard what has been added with the last DRL(s) build. This can be useful to recover from having added an erroneous DRL to the KnowledgeBuilder, as shown below:
kbuilder.add( ResourceFactory.newFileResource( "/project/wrong.drl" ), ResourceType.DRL );
if ( kbuilder.hasErrors() ) {

5.3. ChangeSets

5.3.1. Changesets

The changeset feature facilitates the building of knowledge bases without using the API. Changesets can include any number of resources. They can also support additional configuration information, which currently is only needed for decision tables.
The file changeset.xml contains a list of resources for this. It can also point recursively to another changeset XML file.

5.3.2. Changeset Example

A resource approach is employed that uses a prefix to indicate the protocol. All the protocols provided by java.net.URL, such as "file" and "http", are supported, as well as an additional "classpath". Currently the type attribute must always be specified for a resource, as it is not inferred from the file name extension. This is demonstrated in the example below:
<change-set xmlns='http://drools.org/drools-5.0/change-set'
             xs:schemaLocation='http://drools.org/drools-5.0/change-set http://anonsvn.jboss.org/repos/labs/labs/jbossrules/trunk/drools-api/src/main/resources/change-set-1.0.0.xsd' >
       <resource source='http:org/domain/myrules.drl' type='DRL' />
The above example can be used by changing the resource type to CHANGE_SET:
KnowledgeBuilder kbuilder = KnowledgeBuilderFactory.newKnowledgeBuilder();
kbuilder.add( ResourceFactory.newClasspathResource( "myChangeSet.xml", getClass() ),
              ResourceType.CHANGE_SET );
if ( kbuilder.hasErrors() ) {
    System.err.println( builder.getErrors().toString() );

5.3.3. Extended Changeset Example

ChangeSets can include any number of resources, and they even support additional configuration information, which is only currently needed for decision tables. The example below is expanded to load the rules from a http URL location, and an Excel decision table from the classpath:
<change-set xmlns='http://drools.org/drools-5.0/change-set'
             xs:schemaLocation='http://drools.org/drools-5.0/change-set.xsd http://anonsvn.jboss.org/repos/labs/labs/jbossrules/trunk/drools-api/src/main/resources/change-set-1.0.0.xsd' >
       <resource source='http:org/domain/myrules.drl' type='DRL' />
       <resource source='classpath:data/IntegrationExampleTest.xls' type="DTABLE">
           <decisiontable-conf input-type="XLS" worksheet-name="Tables_2" />

5.3.4. Changesets and Directories Example

You can specify a directory to put content into. It is expected that all the files are of the specified type, since type is not yet inferred from the file name extensions:
<change-set xmlns='http://drools.org/drools-5.0/change-set'
             xs:schemaLocation='http://drools.org/drools-5.0/change-set.xsd http://anonsvn.jboss.org/repos/labs/labs/jbossrules/trunk/drools-api/src/main/resources/change-set-1.0.0.xsd' >
       <resource source='file://myfolder/' type='DRL' />

5.3.5. Building Using Configuration and the ChangeSet XML

You can create definitions using a configuration within the ChangeSet XML. The simple XML file supports three elements: add, remove, and modify. Each of these have a sequence of <resource> subelements defining a configuration entity.
The following example is a none-normative XML schema ChangeSet:
<xs:schema xmlns:xs="http://www.w3.org/2001/XMLSchema"

  <xs:element name="change-set" type="ChangeSet"/>

  <xs:complexType name="ChangeSet">
    <xs:choice maxOccurs="unbounded">
      <xs:element name="add"    type="Operation"/>
      <xs:element name="remove" type="Operation"/>
      <xs:element name="modify" type="Operation"/>

  <xs:complexType name="Operation">
      <xs:element name="resource" type="Resource"

  <xs:complexType name="Resource">
      <!-- To be used with <resource type="DTABLE"...> -->
      <xs:element name="decisiontable-conf" type="DecTabConf"
    <!-- java.net.URL, plus "classpath" protocol -->
    <xs:attribute name="source" type="xs:string"/>
    <xs:attribute name="type"   type="ResourceType"/>

  <xs:complexType name="DecTabConf">
    <xs:attribute name="input-type"     type="DecTabInpType"/>
    <xs:attribute name="worksheet-name" type="xs:string"

  <!-- according to org.drools.builder.ResourceType -->
  <xs:simpleType name="ResourceType">
    <xs:restriction base="xs:string">
      <xs:enumeration value="DRL"/>
      <xs:enumeration value="XDRL"/>
      <xs:enumeration value="DSL"/>
      <xs:enumeration value="DSLR"/>
      <xs:enumeration value="DRF"/>
      <xs:enumeration value="DTABLE"/>
      <xs:enumeration value="PKG"/>
      <xs:enumeration value="BRL"/>
      <xs:enumeration value="CHANGE_SET"/>

  <!-- according to org.drools.builder.DecisionTableInputType -->
  <xs:simpleType name="DecTabInpType">
    <xs:restriction base="xs:string">
      <xs:enumeration value="XLS"/>
      <xs:enumeration value="CSV"/>



Please note, the previous XML schema is for illustration purposes.

5.3.6. ChangeSet XML Example

This is an example of a basic ChangeSet XML schema that loads a single DRL file:
<change-set xmlns='http://drools.org/drools-5.0/change-set'
             xs:schemaLocation='http://drools.org/drools-5.0/change-set.xsd http://anonsvn.jboss.org/repos/labs/labs/jbossrules/trunk/drools-api/src/main/resources/change-set-1.0.0.xsd' >
      <resource source='file:/project/myrules.drl' type='DRL' />

5.3.7. ChangeSet Protocols

The ChangeSet supports all the protocols provided by java.net.URL, such as "file" and "http", as well as an additional "classpath". The type attribute must always be specified for a resource, as it is not inferred from the file name extension.
Use the file: prefix to signify the protocol for the resource.


When using XML schema, the Class Loader will default to the one used by the Knowledge Builder unless the ChangeSet XML is itself loaded by the ClassPath resource, in which case it will use the Class Loader specified for that resource.

5.3.8. Loading the ChangeSet XML

Procedure 5.4. Task

  1. Use the API to load your ChangeSet.
  2. Use this code to access the ChangeSet XML:
    kbuilder.add( ResourceFactory.newUrlResource( url ), ResourceType.CHANGE_SET );

5.3.9. ChangeSet XML with Resource Configuration Example

This example shows you how to incorporate resource configuration in your ChangeSet:
 <change-set xmlns='http://drools.org/drools-5.0/change-set'
             xs:schemaLocation='http://drools.org/drools-5.0/change-set.xsd http://anonsvn.jboss.org/repos/labs/labs/drools/trunk/drools-api/src/main/resources/change-set-1.0.0.xsd' >
       <resource source='http:org/domain/myrules.drl' type='DRL' />
       <resource source='classpath:data/IntegrationExampleTest.xls' type="DTABLE">
           <decisiontable-conf input-type="XLS" worksheet-name="Tables_2" />

5.3.10. ChangeSet XML and Directories

The following code allows you to add a directory's contents to the ChangeSet:
<change-set xmlns='http://drools.org/drools-5.0/change-set'
            xs:schemaLocation='http://drools.org/drools-5.0/change-set.xsd http://anonsvn.jboss.org/repos/labs/labs/drools/trunk/drools-api/src/main/resources/change-set-1.0.0.xsd' >
      <resource source='file:/projects/myproject/myrules' type='DRL' />


Currently it is expected that all resources in that folder are of the same type. If you use the Knowledge Agent it will provide a continuous scanning for added, modified or removed resources and rebuild the cached Knowledge Base.

Chapter 6. Building

6.1. Result Severity

6.1.1. Build Result Severity

You can change the default severity of a type of build result. This can be useful if, for example, a new rule with a duplicate name of an existing rule is added to a package. (In this case, the default behavior is to replace the old rule with the new rule and report it as an INFO.) In some deployments the user might want to prevent the rule update and report it as an error.

6.1.2. Setting the Default Build Result Severity

Procedure 6.1. Task

  1. To configure it using system properties or configuration files, insert the following properties:
    // sets the severity of rule updates
    drools.kbuilder.severity.duplicateRule = <INFO|WARNING|ERROR>
    // sets the severity of function updates
    drools.kbuilder.severity.duplicateFunction = <INFO|WARNING|ERROR>
  2. To use the API to change the severities, use this code:
    KnowledgeBuilderConfiguration kbconf = ...
    // sets the severity of rule updates to error
    kbconf.setOption( KBuilderSeverityOption.get( "drools.kbuilder.severity.duplicateRule", ResultSeverity.ERROR ) ); 
    // sets the severity of function updates to error
    kbconf.setOption( KBuilderSeverityOption.get( "drools.kbuilder.severity.duplicateFunction", ResultSeverity.ERROR ) );

6.2. Building and Deploying

6.2.1. KnowledgePackage

A Knowledge Package is a collection of Knowledge Definitions, such as rules and processes. It is created by the Knowledge Builder. Knowledge Packages are self-contained and serializable, and they currently form the basic deployment unit.
A chart demonstrating the KnowledgePackage interface.

Figure 6.1. KnowledgePackage interface


A Knowledge Package instance cannot be reused once it's added to the Knowledge Base. If you need to add it to another Knowledge Base, serialize it and use the "cloned" result.

6.2.2. Creating a new KnowledgeBase

Procedure 6.2. Task

  1. Use this default configuration to create a new KnowledgeBase:
    KnowledgeBase kbase = KnowledgeBaseFactory.newKnowledgeBase();
  2. If a custom class loader was used with the KnowledgeBuilder to resolve types not in the default class loader, then that must also be set on the KnowledgeBase. The technique for this is the same as with the KnowledgeBuilder and is shown below:
    KnowledgeBaseConfiguration kbaseConf =
        KnowledgeBaseFactory.createKnowledgeBaseConfiguration( null, cl );
    KnowledgeBase kbase = KnowledgeBaseFactory.newKnowledgeBase( kbaseConf );

6.2.3. Add KnowledgePackages to a KnowledgeBase

In-process building is the simplest form of deployment. It compiles the knowledge definitions and adds them to the Knowledge Base in the same JVM. This approach requires drools-core.jar and drools-compiler.jar to be on the classpath.

Procedure 6.3. Task

  • To add KnowledgePackages to a KnowledgeBase, use this code:
    Collection<KnowledgePackage> kpkgs = kbuilder.getKnowledgePackages();
    KnowledgeBase kbase = KnowledgeBaseFactory.newKnowledgeBase();
    kbase.addKnowledgePackages( kpkgs );
    The addKnowledgePackages(kpkgs) method can be called iteratively to add additional knowledge.

6.2.4. Building and Deployment in Separate Processes

Both the KnowledgeBase and the KnowledgePackage are units of deployment and serializable. This means you can have one machine do any necessary building, requiring drools-compiler.jar, and have another machine deploy and execute everything, needing only drools-core.jar.

6.2.5. Writing the KnowledgePackage to an OutputStream

This is the code for writing the KnowledgePackage to an OutputStream:
 ObjectOutputStream out = new ObjectOutputStream( new FileOutputStream( fileName ) );
out.writeObject( kpkgs );

6.2.6. Reading the KnowledgePackage from an InputStream

Use this code for reading the KnowledgePackage from an InputStream:
ObjectInputStream in = new ObjectInputStream( new FileInputStream( fileName ) );
// The input stream might contain an individual
// package or a collection.
@SuppressWarnings( "unchecked" )
Collection<KnowledgePackage> kpkgs =
    ()in.readObject( Collection<KnowledgePackage> );

KnowledgeBase kbase = KnowledgeBaseFactory.newKnowledgeBase();
kbase.addKnowledgePackages( kpkgs );

6.2.7. StatefulknowledgeSessions and KnowledgeBase Modifications

The KnowledgeBase creates and returns StatefulKnowledgeSession objects and can optionally keep references to them.
When KnowledgeBase modifications occur, they are applied against the data in the sessions. This reference is a weak reference and it is also optional. It is controlled by a boolean flag.

6.3. The Knowledge Agent

6.3.1. Knowledge Agent

The Knowledge Agent provides automatic loading, caching and re-loading of resources and is configured from a Knowledge Base properties files. The Knowledge Agent can update or rebuild a Knowledge Base as the resources it uses are changed. The strategy for this is determined by the configuration given to the factory, but it is typically pull-based using regular polling.
Below is a Knowledge Agent example:
KnowledgeAgent kagent = KnowledgeAgentFactory.newKnowledgeAgent( "MyAgent" );
kagent.applyChangeSet( ResourceFactory.newUrlResource( url ) );
KnowledgeBase kbase = kagent.getKnowledgeBase();
The code below is responsible for making a new KnowledgeAgent:
KnowledgeAgent kagent = KnowledgeAgentFactory.newKnowledgeAgent( "MyAgent" );

6.3.2. KnowledgeAgent Objects

A KnowledgeAgent object will continuously scan all resources using a default polling interval of 60 seconds. When a modification date is updated, it will applied the changes into the cached Knowledge Base using the new resources. The previous KnowledgeBase reference will still exist and you'll have to call getKnowledgeBase() to access the newly built KnowledgeBase. If a directory is specified as part of the change set, the entire contents of that directory will be scanned for changes. The way modifications are applied depends on drools.agent.newInstance property present in the KnowledgeAgentConfiguration object passed to the agent.

6.3.3. Writing the KnowledgePackage to an OutputStream

This is how to write the KnowledgePackage to an OutputStream:
KnowledgeAgent kagent = KnowledgeAgentFactory.newKnowledgeAgent( "MyAgent" );
kagent.applyChangeSet( ResourceFactory.newUrlResource( url ) );
KnowledgeBase kbase = kagent.getKnowledgeBase();

6.3.4. ClassLoaders Custom ClassLoaders for KnowledgeBuilder

The Knowledge Agent could end up failing during the compiling or executing process while using classes outside the agent's classloader. If this occurs, use a custom classloader for the Knowledge Agent's kbuilder or force the Knowledge Agent to use the same classloader that its kbase uses.

Procedure 6.4. Custom Classloaders for KnowledgeBuilder

  1. Open a KnowledgeBuilderConfiguration and specify a custom classloader.
  2. If you need to pass custom configuration to these compilers, sends a KnowledgeBuilderConfiguration object to KnowledgeAgentFactory.newKnowledgeAgent().
This object will be used in every builder the agent creates.

Procedure 6.5. Reusing the KnowledgeBase ClassLoader

  1. Determine if the classloader you want to use in the compilation process of remote resources is the same needed in the Knowledge Agent's kbase, so the rules can be executed.
  2. Set up the desired ClassLoader to the agent kbase and use the drools.agent.useKBaseClassLoaderForCompiling property of KnowledgeAgentConfiguration object.
  3. Modify the agent's kbuilder classloader in runtime by modifying the agent's kbase classloader.
The following is an example of the KnowledgeAgentConfiguration property:
KnowledgeBaseConfiguration kbaseConfig =
    KnowledgeBaseFactory.newKnowledgeBaseConfiguration(null, customClassLoader);
KnowledgeBase kbase =
    KnowledgeBaseFactory.newKnowledgeBase(kbaseConfig); //kbase with custom classloader
KnowledgeAgentConfiguration aconf =
aconf.setProperty("drools.agent.newInstance", "false"); //incremental change set processing enabled
aconf.setProperty("drools.agent.useKBaseClassLoaderForCompiling", "true");
KnowledgeAgent kagent = KnowledgeAgentFactory.newKnowledgeAgent(
                "test agent", kbase, aconf);

6.3.5. newInstance The newInstance Property

The newInstance property assists in processing change sets.
A Knowledge Agent can process change sets in two different ways: recreating the knowledge base every time a new change set is processed or applying the change set in the cached knowledge base without destroying it. This behavior is controlled by the KnowledgeAgentConfiguration object's newInstance property when it is passed to the Agent's constructor.

6.3.6. Resource Scanning Starting the Scanning and Notification Services

This is the code for starting scanning and notification services:


Resource scanning is not on by default. It must be started. This also applies to notification. Both can be done via the ResourceFactory. The ResourceChangeScanner

The ResourceChangeScanner is used to scan for services. The default resource scanning period may be changed via the ResourceChangeScannerService. A suitably updated ResourceChangeScannerConfiguration object is passed to the service's configure() method, which allows for the service to be reconfigured on demand. Changing the Scanning Intervals

This is the code to use to change scanning intervals:
ResourceChangeScannerConfiguration sconf =
// Set the disk scanning interval to 30s, default is 60s.
sconf.setProperty( "drools.resource.scanner.interval", "30" ); 
ResourceFactory.getResourceChangeScannerService().configure( sconf ); The KnowledgeAgentConfiguration Property

The KnowledgeAgentConfiguration can be used to modify a Knowledge Agent's default behavior. You can use this to load the resources from a directory while inhibiting the continuous scan for changes of that directory. Change the Scanning Behavior

Use this code to change the scanning behavior:
KnowledgeBase kbase = KnowledgeBaseFactory.newKnowledgeBase();

KnowledgeAgentConfiguration kaconf =
// Do not scan directories, just files.
kaconf.setProperty( "drools.agent.scanDirectories", "false" );
KnowledgeAgent kagent =
    KnowledgeAgentFactory.newKnowledgeAgent( "test agent", kaconf );

6.3.7. Knowledge Bases and applyChangeSet() Interactions Between Knowledge Agents and Knowledge Bases

Knowledge Agents can process both an empty Knowledge Base or a populated one. If a populated Knowledge Base is provided, the Knowledge Agent will run an iterator from Knowledge Base and subscribe to the resources that it finds. While it is possible for the Knowledge Builder to build all resources found in a directory, that information is lost by the Knowledge Builder so that those directories will not be continuously scanned. Only directories specified as part of the applyChangeSet(Resource) method are monitored.
One of the advantages of providing KnowledgeBase as the starting point is that you can provide it with a KnowledgeBaseConfiguration. When resource changes are detected and a new KnowledgeBase object is instantiated, it will use the KnowledgeBaseConfiguration of the previous KnowledgeBase object. Using an Existing KnowledgeBase

This is the code for utilizing an existing KnowledgeBase:
KnowledgeBaseConfiguration kbaseConf =
    KnowledgeBaseFactory.createKnowledgeBaseConfiguration( null, cl );
KnowledgeBase kbase KnowledgeBaseFactory.newKnowledgeBase( kbaseConf );
// Populate kbase with resources here.

KnowledgeAgent kagent =
    KnowledgeAgentFactory.newKnowledgeAgent( "MyAgent", kbase );
KnowledgeBase kbase = kagent.getKnowledgeBase();
In the above example getKnowledgeBase() will return the same provided kbase instance until resource changes are detected and a new Knowledge Base is built. When the new Knowledge Base is built, it will be done with the KnowledgeBaseConfiguration that was provided to the previous KnowledgeBase. The applyChangeSet() Method

If a ChangeSet XML is used with the applyChangeSet() method it will add any directories to the scanning process. When the directory scan detects an additional file, it will be added to the Knowledge Base. Any removed file is removed from the Knowledge Base, and modified files will be removed from the Knowledge Base. ChangeSet XML to Add Directory Contents

Use this XML to add the contents of a directory to a ChangeSet:
<change-set xmlns='http://drools.org/drools-5.0/change-set'
            xs:schemaLocation='http://drools.org/drools-5.0/change-set.xsd' >
      <resource source='file:/projects/myproject/myrules' type='PKG' />


Note that for the resource type PKG, the drools-compiler dependency is not needed. The Knowledge Agent is able to handle those with just drools-core.

6.3.8. Resource Caching Restoring Resource Caching After a Restart

If your knowledge agent is pulling resources from an http(s) URL, the resource from the remote web server may suddenly disappear.

Procedure 6.6. Resource Restart

  1. To survive a restart when a resource is no longer available remotely (for example, the remote server is being restarted), set a System Property: drools.resource.urlcache.
  2. Make sure that System Property is set to a directory that has write permissions for the application. The Knowledge Agent will cache copies of the remote resources in that directory.
  3. Using the java command line -Ddrools.resource.urlcache=/users/someone/KnowledgeCache - will keep local copies of the resources (rules, packages etc) in that directory for the agent to use should it be restarted. (When a remote resource becomes available, and is updated, it will automatically update the local cache copy.)

Chapter 7. Sessions

7.1. Sessions in JBoss Rules

Sessions are created from the KnowledgeBase into which data can be inserted and from which process instances may be started. Creating the KnowledgeBase can be resource-intensive, whereas session creation is not. For this reason, it is recommended that KnowledgeBases be cached where possible to allow for repeated session creation.

7.2. Create a StatefulKnowledgeSession From a KnowledgeBase

Created from the KnowledgeBase, the StatefulKnowledgeSession stores and executes on the runtime data. Below is the code for creating a new StatefulKnowledgeSession from a KnowledgeBase:
StatefulKnowledgeSession ksession = kbase.newStatefulKnowledgeSession();

7.3. KnowledgeRuntime

7.3.1. The WorkingMemoryEntryPoint Method

The WorkingMemoryEntryPoint provides the methods around inserting, updating and retrieving facts. The term "entry point" is related to the fact that there are multiple partitions in a Working Memory and you can choose which one you are inserting into. Most rule based applications will work with the default entry point alone.

7.3.2. The KnowledgeRuntime Interface

The KnowledgeRuntime interface provides the main interaction with the engine. It is available in rule consequences and process actions. The KnowledgeRuntime inherits methods from both the WorkingMemory and the ProcessRuntime, thereby providing a unified API to work with processes and rules. When working with rules, three interfaces form the KnowledgeRuntime: WorkingMemoryEntryPoint, WorkingMemory and the KnowledgeRuntime itself.

7.3.3. Fact Insertion

Insertion is the act of telling the WorkingMemory about a fact. You can do this by using ksession.insert(yourObject), for example. When you insert a fact, it is examined for matches against the rules. This means all of the work for deciding about firing or not firing a rule is done during insertion. However, no rule is executed until you call fireAllRules(), which you call after you have finished inserting your facts.

7.3.4. The FactHandle Token

When an Object is inserted, it returns a FactHandle. This FactHandle is the token used to represent your inserted object within the WorkingMemory. It is also used for interactions with the WorkingMemory when you wish to retract or modify an object. Below is an example of code implementing a FactHandle:
Job accountant = new Job("accountant");
FactHandle accountantHandle = ksession.insert( accountant );

7.3.5. Identity and Equality

These are the two assertation nodes used by the Working Memory:
This means that the Working Memory uses an IdentityHashMap to store all asserted objects. New instance assertions always result in the return of new FactHandle, but if an instance is asserted again then it returns the original fact handle (that is, it ignores repeated insertions for the same object).
This means that the Working Memory uses a HashMap to store all asserted objects. An object instance assertion will only return a new FactHandle if the inserted object is not equal (according to its equal method) to an already existing fact.


New instance assertions always result in the return of new FactHandle, but if an instance is asserted again then it returns the original fact handle (that is, it ignores repeated insertions for the same object).

7.3.6. Retraction

Retraction is the removal of a fact from Working Memory. This means that it will no longer track and match that fact, and any rules that are activated and dependent on that fact will be canceled. It is possible to have rules that depend on the nonexistence of a fact, in which case retracting a fact may cause a rule to activate. Retraction may be done using the FactHandle that was returned by the insert call. On the right hand side of a rule the retract statement is used, which works with a simple object reference. Implemented below is example Retraction code:
Job accountant = new Job("accountant");
FactHandle accountantHandle = ksession.insert( accountant );
ksession.retract( accountantHandle );

7.3.7. The update() Method

The Rule Engine must be notified of modified facts so they can be reprocessed. The update() method can be used to notify the WorkingMemory of changed objects for those objects that are not able to notify the WorkingMemory themselves. The update() method always takes the modified object as a second parameter, which allows you to specify new instances for immutable objects. The following is an update() example:
Job accountant = new Job("accountant");
FactHandle accountantHandle = workingMemory.insert( accountant );
accountant.setSalary( 45000 );
workingMemory.update( accountantHandle, accountant );


On the right hand side of a rule the modify statement is recommended, as it makes the changes and notifies the engine in a single statement. Alternatively, after changing a fact object's field values through calls of setter methods you must invoke update immediately, event before changing another fact, or you will cause problems with the indexing within the rule engine. The modify statement avoids this problem.

7.4. Working Memory

7.4.1. Queries

Queries are used to retrieve fact sets based on patterns, as they are used in rules. Patterns may make use of optional parameters. Queries can be defined in the Knowledge Base, from where they are called up to return the matching results. While iterating over the result collection, any identifier bound in the query can be used to access the corresponding fact or fact field by calling the get method with the binding variable's name as its argument. If the binding refers to a fact object, its FactHandle can be retrieved by calling getFactHandle, again with the variable's name as the parameter. Illustrated below is a Query example:
QueryResults results =
    ksession.getQueryResults( "my query", new Object[] { "string" } );
for ( QueryResultsRow row : results ) {
    System.out.println( row.get( "varName" ) );

7.4.2. Live Queries

Invoking queries and processing the results by iterating over the returned set is not a good way to monitor changes over time.
To alleviate this, JBoss Rules provides Live Queries, which have a listener attached instead of returning an iterable result set. These live queries stay open by creating a view and publishing change events for the contents of this view. To activate, start your query with parameters and listen to changes in the resulting view. The dispose method terminates the query and discontinues this reactive scenario.

7.4.3. ViewChangedEventListener Implementation Example

final List updated = new ArrayList();
final List removed = new ArrayList();
final List added = new ArrayList();
ViewChangedEventListener listener = new ViewChangedEventListener() {           
 public void rowUpdated(Row row) {
  updated.add( row.get( "$price" ) );
 public void rowRemoved(Row row) {
  removed.add( row.get( "$price" ) );
 public void rowAdded(Row row) {
  added.add( row.get( "$price" ) );
// Open the LiveQuery
LiveQuery query = ksession.openLiveQuery( "cars",
                                          new Object[] { "sedan", "hatchback" },
                                          listener );
query.dispose() // calling dispose to terminate the live query


For an example of Glazed Lists integration for live queries, visit http://blog.athico.com/2010/07/glazed-lists-examples-for-drools-live.html

7.5. KnowledgeRuntime

The KnowledgeRuntime provides further methods that are applicable to both rules and processes, such as setting globals and registering channels. ("Exit point" is an obsolete synonym for "channel".)

Chapter 8. Objects and Interfaces

8.1. Globals

Globals are named objects that are made visible to the rule engine, but unlike facts, changes in the object backing a global do not trigger reevaluation of rules. Globals are useful for providing static information, as an object offering services that are used in the RHS of a rule, or as a means to return objects from the rule engine. When you use a global on the LHS of a rule, make sure it is immutable, or else your changes will not have any effect on the behavior of your rules.

8.2. Working With Globals

Procedure 8.1. Task

  1. To start implementing globals into the Working Memory, declare a global in a rules file and back it up with a Java object:
    global java.util.List list
  2. With the Knowledge Base now aware of the global identifier and its type, you can call ksession.setGlobal() with the global's name and an object (for any session) to associate the object with the global:
    List list = new ArrayList();
    ksession.setGlobal("list", list);


    Failure to declare the global type and identifier in DRL code will result in an exception being thrown from this call.
  3. Set the global before it is used in the evaluation of a rule. Failure to do so results in a NullPointerException.

8.3. Resolving Globals

Globals can be resolved in three ways:
The Stateless Knowledge Session method getGlobals() returns a Globals instance which provides access to the session's globals. These are shared for all execution calls. Exercise caution regarding mutable globals because execution calls can be executing simultaneously in different threads.
Using a delegate is another way of providing global resolution. Assigning a value to a global (with setGlobal(String, Object)) results in the value being stored in an internal collection mapping identifiers to values. Identifiers in this internal collection will have priority over any supplied delegate. If an identifier cannot be found in this internal collection, the delegate global (if any) will be used.
Execution scoped globals use a Command to set a global which is then passed to the CommandExecutor.

8.4. Session Scoped Global Example

This is what a session scoped Global looks like:
StatelessKnowledgeSession ksession = kbase.newStatelessKnowledgeSession();
// Set a global hbnSession, that can be used for DB interactions in the rules.
ksession.setGlobal( "hbnSession", hibernateSession );
// Execute while being able to resolve the "hbnSession" identifier.  
ksession.execute( collection );

8.5. StatefulRuleSessions

The StatefulRuleSession property is inherited by the StatefulKnowledgeSession and provides the rule-related methods that are relevant from outside of the engine.

8.6. AgendaFilter Objects

AgendaFilter objects are optional implementations of the filter interface which are used to allow or deny the firing of an activation. What is filtered depends on the implementation.

8.7. Using the AgendaFilter

Procedure 8.2. Task

  • To use a filter specify it while calling fireAllRules(). The following example permits only rules ending in the string "Test". All others will be filtered out:
    ksession.fireAllRules( new RuleNameEndsWithAgendaFilter( "Test" ) );

8.8. Rule Engine Phases

The engine cycles repeatedly through two phases:
Working Memory Actions
This is where most of the work takes place, either in the Consequence (the RHS itself) or the main Java application process. Once the Consequence has finished or the main Java application process calls fireAllRules() the engine switches to the Agenda Evaluation phase.
Agenda Evaluation
This attempts to select a rule to fire. If no rule is found it exits. Otherwise it fires the found rule, switching the phase back to Working Memory Actions.
The process repeats until the agenda is clear, in which case control returns to the calling application. When Working Memory Actions are taking place, no rules are being fired.

8.9. The Event Model

The event package provides means to be notified of rule engine events, including rules firing, objects being asserted, etc. This allows you, for instance, to separate logging and auditing activities from the main part of your application (and the rules).

8.10. The KnowlegeRuntimeEventManager

The KnowlegeRuntimeEventManager interface is implemented by the KnowledgeRuntime which provides two interfaces, WorkingMemoryEventManager and ProcessEventManager.

8.11. The WorkingMemoryEventManager

The WorkingMemoryEventManager allows for listeners to be added and removed, so that events for the working memory and the agenda can be listened to.

8.12. Adding an AgendaEventListener

The following code snippet shows how a simple agenda listener is declared and attached to a session. It will print activations after they have fired:
ksession.addEventListener( new DefaultAgendaEventListener() {
   public void afterActivationFired(AfterActivationFiredEvent event) {
       super.afterActivationFired( event );
       System.out.println( event );

8.13. Printing Working Memory Events

This code lets you print all Working Memory events by adding a listener:
ksession.addEventListener( new DebugWorkingMemoryEventListener() );

8.14. KnowlegeRuntimeEvents

All emitted events implement the KnowlegeRuntimeEvent interface which can be used to retrieve the actual KnowlegeRuntime the event originated from.

8.15. Supported Events for the KnowledgeRuntimeEvent Interface

The events currently supported are:
  • ActivationCreatedEvent
  • ActivationCancelledEvent
  • BeforeActivationFiredEvent
  • AfterActivationFiredEvent
  • AgendaGroupPushedEvent
  • AgendaGroupPoppedEvent
  • ObjectInsertEvent
  • ObjectRetractedEvent
  • ObjectUpdatedEvent
  • ProcessCompletedEvent
  • ProcessNodeLeftEvent
  • ProcessNodeTriggeredEvent
  • ProcessStartEvent

8.16. The KnowledgeRuntimeLogger

The KnowledgeRuntimeLogger uses the comprehensive event system in JBoss Rules to create an audit log that can be used to log the execution of an application for later inspection, using tools such as the Eclipse audit viewer.

8.17. Enabling a FileLogger

To enable a FileLogger to track your files, use this code:
KnowledgeRuntimeLogger logger =
  KnowledgeRuntimeLoggerFactory.newFileLogger(ksession, "logdir/mylogfile");

8.18. Using StatelessKnowledgeSession in JBoss Rules

The StatelessKnowledgeSession wraps the StatefulKnowledgeSession, instead of extending it. Its main focus is on decision service type scenarios. It avoids the need to call dispose(). Stateless sessions do not support iterative insertions and the method call fireAllRules() from Java code. The act of calling execute() is a single-shot method that will internally instantiate a StatefulKnowledgeSession, add all the user data and execute user commands, call fireAllRules(), and then call dispose(). While the main way to work with this class is via the BatchExecution (a subinterface of Command) as supported by the CommandExecutor interface, two convenience methods are provided for when simple object insertion is all that's required. The CommandExecutor and BatchExecution are talked about in detail in their own section.

8.19. Performing a StatelessKnowledgeSession Execution with a Collection

This the code for performing a StatelessKnowledgeSession execution with a collection:
KnowledgeBuilder kbuilder = KnowledgeBuilderFactory.newKnowledgeBuilder();
kbuilder.add( ResourceFactory.newFileSystemResource( fileName ), ResourceType.DRL );
if (kbuilder.hasErrors() ) {
    System.out.println( kbuilder.getErrors() );
} else {
    KnowledgeBase kbase = KnowledgeBaseFactory.newKnowledgeBase();
    kbase.addKnowledgePackages( kbuilder.getKnowledgePackages() );
    StatelessKnowledgeSession ksession = kbase.newStatelessKnowledgeSession();
    ksession.execute( collection );

8.20. Performing a StatelessKnowledgeSession Execution with the InsertElements Command

This is the code for performing a StatelessKnowledgeSession execution with the InsertElements Command:
ksession.execute( CommandFactory.newInsertElements( collection ) );


To insert the collection and its individual elements, use CommandFactory.newInsert(collection).

8.21. The BatchExecutionHelper

Methods of the CommandFactory create the supported commands, all of which can be marshaled using XStream and the BatchExecutionHelper. BatchExecutionHelper provides details on the XML format as well as how to use JBoss Rules Pipeline to automate the marshaling of BatchExecution and ExecutionResults.

8.22. The CommandExecutor Interface

The CommandExecutor interface allows users to export data using "out" parameters. This means that inserted facts, globals and query results can all be returned using this interface.

8.23. Out Identifiers

This is an example of what out identifiers look like:
// Set up a list of commands
List cmds = new ArrayList();
cmds.add( CommandFactory.newSetGlobal( "list1", new ArrayList(), true ) );
cmds.add( CommandFactory.newInsert( new Person( "jon", 102 ), "person" ) );
cmds.add( CommandFactory.newQuery( "Get People" "getPeople" );

// Execute the list
ExecutionResults results =
  ksession.execute( CommandFactory.newBatchExecution( cmds ) );

// Retrieve the ArrayList
results.getValue( "list1" );
// Retrieve the inserted Person fact
results.getValue( "person" );
// Retrieve the query as a QueryResults instance.
results.getValue( "Get People" );

Chapter 9. Modes and Methods

9.1. Sequential Mode

Using sequential mode in JBoss Rules allows you to utilize the engine in a more simplified way. It allows for rules to be used without needing to be re-evaluated if a user is working with a stateless session and no more data can be asserted or modified after the initial data set.

9.2. Sequential Mode Options

These are some of the options you can choose to utilize when using the sequential mode:
  1. Order the Rules by salience and position in the ruleset (by setting a sequence attribute on the rule terminal node).
  2. Create an array (one element for each possible rule activation). Element position indicates firing order.
  3. Turn off all node memories, except the right-input Object memory.
  4. Disconnect the Left Input Adapter Node propagation and let the Object and the Node be referenced in a Command object. This is added to a list in the Working Memory for later execution.
  5. Assert all objects. When all assertions are finished and the right-input node memories are populated, you can check the Command list and execute each in turn.
  6. All resulting Activations should be placed in the array, based upon the determined sequence number of the Rule. Record the first and last populated elements, to reduce the iteration range.
  7. Iterate the array of Activations, executing populated element in turn.
  8. If there is a maximum number of allowed rule executions, exit the network evaluations early to fire all the rules in the array.

9.3. Activating Sequential Mode

Procedure 9.1. Task

  1. Start a stateless session.
  2. The sequential mode will be turned off by default. To turn it on, call RuleBaseConfiguration.setSequential(true). Alternatively, set the rulebase configuration property drools.sequential to true.
  3. To allow sequential mode to fall back to a dynamic agenda, call setSequentialAgenda with SequentialAgenda.DYNAMIC.
  4. Optionally, set the JBossRules.sequential.agenda property to sequential or dynamic.

9.4. The CommandFactory

The CommandFactory object allows for commands to be executed on stateless sessions. Upon its conclusion, the factory will execute fireAllRules() before disposing the session.

9.5. Supported CommandFactory Options

All of these options are compatible with the CommandFactory:
  • FireAllRules
  • GetGlobal
  • SetGlobal
  • InsertObject
  • InsertElements
  • Query
  • StartProcess
  • BatchExecution

9.6. The Insert Command

InsertObject will insert a single object with an optional "out" identifier. InsertElements will iterate an Iterable, inserting each of the elements. This allows a Stateless Knowledge Session to process or execute queries in any order.

9.7. Insert Command Example

StatelessKnowledgeSession ksession = kbase.newStatelessKnowledgeSession();
ExecutionResults bresults =
  ksession.execute( CommandFactory.newInsert( new Car( "sedan" ), "sedan_id" ) );
Sedan sedan = bresults.getValue( "sedan_id" );

9.8. The Execute Method

The execute method is used to execute commands one at a time. It always returns an ExecutionResults instance, which allows access to any command results if they specify an out identifier such as stilton_id.

9.9. Execute Method Example

StatelessKnowledgeSession ksession = kbase.newStatelessKnowledgeSession();
Command cmd = CommandFactory.newInsertElements( Arrays.asList( Object[] { 
                  new Car( "sedan" ),
                  new Car( "hatchback" ),
                  new Car( "convertible" ),
ExecutionResults bresults = ksession.execute( cmd );

9.10. The BatchExecution Command

The BatchExecution command allows you to execute multiple commands at once. It represents a composite command that is created from a list of commands. Execute will iterate over the list and execute each command in turn. This means you can insert some objects, start a process, call fireAllRules and execute a query, all in a single execute(...) call.

9.11. The FireAllRules Command

The FireAllRules command disables the automatic execution of rules at the end. It is a type of manual override function.

9.12. Out Identifiers

Commands support out identifiers. Any command that has an out identifier set on it will add its results to the returned ExecutionResults instance.

9.13. Out Identifier Example

This example will use the BatchExecution command to show how out identifiers work:
StatelessKnowledgeSession ksession = kbase.newStatelessKnowledgeSession();

List cmds = new ArrayList();        
cmds.add( CommandFactory.newInsertObject( new Car( "red", 1), "red") );
cmds.add( CommandFactory.newStartProcess( "process cars" ) );
cmds.add( CommandFactory.newQuery( "cars" ) );
ExecutionResults bresults = ksession.execute( CommandFactory.newBatchExecution( cmds ) );
Car red = ( Car ) bresults.getValue( "red" );
QueryResults qresults = ( QueryResults ) bresults.getValue( "cars" );
In the above example multiple commands are executed, two of which populate the ExecutionResults. The query command defaults to use the same identifier as the query name, but it can also be mapped to a different identifier.

9.14. Execution XML Examples

A custom XStream marshaler can be used with the JBoss Rules Pipeline to achieve XML scripting, which is perfect for services. Here are two examples of this:
BatchExecution XML:
   <insert out-identifier='outRed'>
ExecutionResults XML:
   <result identifier='outBlue'>

9.15. Execution Marshalling Examples

This is an example of BatchExecution marshalled to XML
  <insert out-identifier="sedan">
  <query out-identifier='cars2' name='carsWithParams'>
The CommandExecutor returns an ExecutionResults, and this is handled by the pipeline code snippet as well. A similar output for the <batch-execution> XML sample above would be:
  <result identifier="sedan">
  <result identifier='cars2'>

9.16. Batch-execution and Command Examples

  1. There is currently no XML schema to support schema validation. This is the basic format. The root element is <batch-execution> and it can contain zero or more commands elements:
  2. The insert element features an "out-identifier" attribute so the inserted object will be returned as part of the result payload:
       <insert out-identifier='userVar'>
  3. It's also possible to insert a collection of objects using the <insert-elements> element. This command does not support an out-identifier. The org.domain.UserClass is just an illustrative user object that XStream would serialize:
  4. The <set-global> element sets a global for the session:
       <set-global identifier='userVar'>
  5. <set-global> also supports two other optional attributes: out and out-identifier. A true value for the boolean out will add the global to the <batch-execution-results> payload, using the name from the identifier attribute. out-identifier works like out but additionally allows you to override the identifier used in the <batch-execution-results> payload:
       <set-global identifier='userVar1' out='true'>
       <set-global identifier='userVar2' out-identifier='alternativeUserVar2'>
  6. There is a <get-global> element without contents. It only has an out-identifier attribute. There is no need for an out attribute because retrieving the value is the sole purpose of a <get-global> element:
       <get-global identifier='userVar1' />
       <get-global identifier='userVar2' out-identifier='alternativeUserVar2'/>
  7. The query command supports both parameter and parameterless queries. The name attribute is the name of the query to be called, and the out-identifier is the identifier to be used for the query results in the <execution-results> payload:
       <query out-identifier='cars' name='cars'/>
       <query out-identifier='cars2' name='carsWithParams'>
  8. The <start-process> command accepts optional parameters:
       <startProcess processId='org.drools.actions'>
          <parameter identifier='person'>
                <name>John Doe</name>
  9. The signal event command allows you to identify processes:
    <signal-event process-instance-id='1' event-type='MyEvent'>
  10. The complete work item command notifies users when a process is completed:
    <complete-work-item id='" + workItem.getId() + "' >
       <result identifier='Result'>
  11. The abort work item command lets you cancel a process while it is running:
    <abort-work-item id='21' />

9.17. The MarshallerFactory

The MarshallerFactory is used to marshal and unmarshal Stateful Knowledge Sessions.

9.18. Marshaller Example

This is what a marsheller looks like in practice:
// ksession is the StatefulKnowledgeSession
// kbase is the KnowledgeBase
ByteArrayOutputStream baos = new ByteArrayOutputStream();
Marshaller marshaller = MarshallerFactory.newMarshaller( kbase );
marshaller.marshall( baos, ksession );

9.19. Marshalling Options

Table 9.1. ** table title **

Option Description
ObjectMarshallingStrategy This interface provides implementations for marshalling and allows for greater flexibility.
This is the default strategy for calling the Serializable or Externalizable methods on a user instance.
This strategy creates an integer id for each user object and stores them in a Map, while the id is written to the stream.
When unmarshalling it accesses the IdentityMarshallingStrategy map to retrieve the instance. This means that if you use the IdentityMarshallingStrategy, it is stateful for the life of the Marshaller instance and will create ids and keep references to all objects that it attempts to marshal.

9.20. IdentityMarshallingStrategy Example

This is the code for using the IdentityMarshallingStrategy:
ByteArrayOutputStream baos = new ByteArrayOutputStream();
ObjectMarshallingStrategy oms = MarshallerFactory.newIdentityMarshallingStrategy()
Marshaller marshaller =
  MarshallerFactory.newMarshaller( kbase, new ObjectMarshallingStrategy[]{ oms } );
marshaller.marshall( baos, ksession );

9.21. The ObjectMarshallingStrategyAcceptor

The ObjectMarshallingStrategyAcceptor is the interface that each Object Marshalling Strategy contains. The Marshaller has a chain of strategies. When it attempts to read or write a user object, it uses the ObjectMarshallingStrategyAcceptor to determine if they are to be used for marshalling the user object.

9.22. The ClassFilterAcceptor Implementation

The ClassFilterAcceptor implementation allows strings and wild cards to be used to match class names. The default is "*.*".

9.23. IdentityMarshallingStrategy with Acceptor Example

This is an example of using the IdentityMarshallingStrategy with the acceptor. Note that the acceptance checking order is in the natural order of the supplied array:
ByteArrayOutputStream baos = new ByteArrayOutputStream();
ObjectMarshallingStrategyAcceptor identityAcceptor =
  MarshallerFactory.newClassFilterAcceptor( new String[] { "org.domain.pkg1.*" } );
ObjectMarshallingStrategy identityStrategy =
  MarshallerFactory.newIdentityMarshallingStrategy( identityAcceptor );
ObjectMarshallingStrategy sms = MarshallerFactory.newSerializeMarshallingStrategy();
Marshaller marshaller =
  MarshallerFactory.newMarshaller( kbase,
                                   new ObjectMarshallingStrategy[]{ identityStrategy, sms } );
marshaller.marshall( baos, ksession );

9.24. Persistence and Transactions in JBoss Rules

Long-term out of the box persistence with Java Persistence API (JPA) is possible with JBoss Rules. You will need to have some implementation of the Java Transaction API (JTA) installed. For development purposes you can use the Bitronix Transaction Manager as it's simple to set up and works embedded. For production use, JBoss Transactions is recommended.

9.25. Transaction Example

This is what performing a transaction looks like:
Environment env = KnowledgeBaseFactory.newEnvironment();
env.set( EnvironmentName.ENTITY_MANAGER_FACTORY,
         Persistence.createEntityManagerFactory( "emf-name" ) );
env.set( EnvironmentName.TRANSACTION_MANAGER,
         TransactionManagerServices.getTransactionManager() );
// KnowledgeSessionConfiguration may be null, and a default will be used
StatefulKnowledgeSession ksession =
  JPAKnowledgeService.newStatefulKnowledgeSession( kbase, null, env );
int sessionId = ksession.getId();
UserTransaction ut =
  (UserTransaction) new InitialContext().lookup( "java:comp/UserTransaction" );
ksession.insert( data1 );
ksession.insert( data2 );
ksession.startProcess( "process1" );

9.26. Using a JPA

Procedure 9.2. Task

  1. Make sure the environment is set with both the EntityManagerFactory and the TransactionManager.
  2. Launch the JPA from your GUI or command line.
  3. Use the id to load a previously persisted Stateful Knowledge Session. If rollback occurs the ksession state is also rolled back, you can continue to use it after a rollback.

9.27. Loading a StatefulKnowledgeSession with JPA

This is the code for loading a StatefulKnowledgeSession implementing the JPA:
StatefulKnowledgeSession ksession =
  JPAKnowledgeService.loadStatefulKnowledgeSession( sessionId, kbase, null, env );

9.28. Configuring JPA

To enable persistence several classes must be added to your persistence.xml, as in the example below:
<persistence-unit name="org.drools.persistence.jpa" transaction-type="JTA">
         <property name="hibernate.dialect" value="org.hibernate.dialect.H2Dialect"/>            
         <property name="hibernate.max_fetch_depth" value="3"/>
         <property name="hibernate.hbm2ddl.auto" value="update" />
         <property name="hibernate.show_sql" value="true" />
         <property name="hibernate.transaction.manager_lookup_class"
                      value="org.hibernate.transaction.BTMTransactionManagerLookup" />

9.29. Configuring JTA DataSource

This is the code for configuring the JTA DataSource:
PoolingDataSource ds = new PoolingDataSource();
ds.setUniqueName( "jdbc/BitronixJTADataSource" );
ds.setClassName( "org.h2.jdbcx.JdbcDataSource" );
ds.setMaxPoolSize( 3 );
ds.setAllowLocalTransactions( true );
ds.getDriverProperties().put( "user", "sa" );
ds.getDriverProperties().put( "password", "sasa" );
ds.getDriverProperties().put( "URL", "jdbc:h2:mem:mydb" );

9.30. JNDI Properties

Bitronix also provides a simple embedded JNDI service, ideal for testing. To use it add a jndi.properties file to your META-INF and add the following line to it:

9.31. KnowledgeBase Namespaces

This is a list of namespaces you can attach to the KnowledgeBase for building purposes:
  • deftemplate
  • defrule
  • deffunction
  • and/or/not/exists/test conditional elements
  • Literal, Variable, Return Value and Predicate field constraints

Chapter 10. Functions

10.1. Functions

Functions are a way to put semantic code in a rule source file, as opposed to in normal Java classes. The main advantage of using functions in a rule is that you can keep the logic all in one place. You can change the functions as needed.
Functions are most useful for invoking actions on the consequence (then) part of a rule, especially if that particular action is used repeatedly.

10.2. Function Declaration Example

A typical function declaration looks like this:
function String hello(String name) {
    return "Hello "+name+"!";


Note that the function keyword is used, even though it's not technically part of Java. Parameters to the function are defined as for a method. You don't have to have parameters if they are not needed. The return type is defined just like in a regular method.

10.3. Function Declaration with Static Method Example

This example of a function declaration shows the static method in a helper class (Foo.hello(). JBoss Rules supports the use of function imports, so the following code is all you would need to enter the following:
import function my.package.Foo.hello

10.4. Calling a Function Declaration Example

Irrespective of the way the function is defined or imported, you use a function by calling it by its name, in the consequence or inside a semantic code block. This is shown below:
rule "using a static function"
    eval( true )
    System.out.println( hello( "Bob" ) );

10.5. Type Declarations

Type declarations have two main goals in the rules engine: to allow the declaration of new types, and to allow the declaration of metadata for types.

10.6. Type Declaration Roles

Table 10.1. ** table title **

Role Description
Declaring new types
JBoss Rules out of the box with plain Java objects as facts. However, should a user wish to define the model directly to the rules engine, they can do so by declaring a new type. This can also be used when there is a domain model already built, but the user wants to complement this model with additional entities that are used mainly during the reasoning process.
Declaring metadata
Facts may have meta information associated to them. Examples of meta information include any kind of data that is not represented by the fact attributes and is consistent among all instances of that fact type. This meta information may be queried at runtime by the engine and used in the reasoning process.

10.7. Declaring New Types

To declare a new type, the keyword declare is used, followed by the list of fields and the keyword end. A new fact must have a list of fields, otherwise the engine will look for an existing fact class in the classpath and raise an error if not found.

10.8. Declaring a New Fact Type Example

In this example, a new fact type called Address is used. This fact type will have three attributes: number, streetName and city. Each attribute has a type that can be any valid Java type, including any other class created by the user or other fact types previously declared:
declare Address
   number : int
   streetName : String
   city : String

10.9. Declaring a New Fact Type Additional Example

This fact type declaration uses a Person example. dateOfBirth is of the type java.util.Date (from the Java API) and address is of the fact type Address.
declare Person
    name : String
    dateOfBirth : java.util.Date
    address : Address

10.10. Using Import Example

This example illustrates how to use the import feature to avoid he need to use fully qualified class names:
import java.util.Date

declare Person
    name : String
    dateOfBirth : Date
    address : Address

10.11. Generated Java Classes

When you declare a new fact type, JBoss Rules generate bytecode that implements a Java class representing the fact type. The generated Java class will be a one-to-one Java Bean mapping of the type definition.

10.12. Generated Java Class Example

This is an example of a generated Java class using the Person fact type:
public class Person implements Serializable {
    private String name;
    private java.util.Date dateOfBirth;
    private Address address;

    // empty constructor
    public Person() {...}

    // constructor with all fields 
    public Person( String name, Date dateOfBirth, Address address ) {...}

    // if keys are defined, constructor with keys
    public Person( ...keys... ) {...}

    // getters and setters
    // equals/hashCode
    // toString

10.13. Using the Declared Types in Rules Example

Since the generated class is a simple Java class, it can be used transparently in the rules like any other fact:
rule "Using a declared Type"
    $p : Person( name == "Bob" )
    // Insert Mark, who is Bob's manager.
    Person mark = new Person();
    insert( mark );

10.14. Declaring Metadata

Metadata may be assigned to several different constructions in JBoss Rules: fact types, fact attributes and rules. JBoss Rules uses the at sign ('@') to introduce metadata and it always uses the form:
@metadata_key( metadata_value )
The parenthesized metadata_value is optional.

10.15. Working with Metadata Attributes

JBoss Rules allows the declaration of any arbitrary metadata attribute, but some will have special meaning to the engine, while others are simply available for querying at runtime. JBoss Rules allows the declaration of metadata both for fact types and for fact attributes. Any metadata that is declared before the attributes of a fact type are assigned to the fact type, while metadata declared after an attribute are assigned to that particular attribute.

10.16. Declaring a Metadata Attribute with Fact Types Example

This is an example of declaring metadata attributes for fact types and attributes. There are two metadata items declared for the fact type (@author and @dateOfCreation) and two more defined for the name attribute (@key and @maxLength). The @key metadata has no required value, and so the parentheses and the value were omitted:
import java.util.Date

declare Person
    @author( Bob )
    @dateOfCreation( 01-Feb-2009 )

    name : String @key @maxLength( 30 )
    dateOfBirth : Date 
    address : Address

10.17. The @position Attribute

The @position attribute can be used to declare the position of a field, overriding the default declared order. This is used for positional constraints in patterns.

10.18. @position Example

This is what the @position attribute looks like in use:
declare Cheese
    name : String @position(1)
    shop : String @position(2)
    price : int @position(0)

10.19. Predefined Class Level Annotations

Table 10.2. Predefined Class Level Annotations

Annotation Description
@role( <fact | event> )
This attribute can be used to assign roles to facts and events.
@typesafe( <boolean> )
By default, all type declarations are compiled with type safety enabled. @typesafe( false ) provides a means to override this behavior by permitting a fall-back, to type unsafe evaluation where all constraints are generated as MVEL constraints and executed dynamically. This is useful when dealing with collections that do not have any generics or mixed type collections.
@timestamp( <attribute name> )
Creates a timestamp.
@duration( <attribute name> )
Sets a duration for the implementation of an attribute.
@expires( <time interval> )
Allows you to define when the attribute should expire.
Facts that implement support for property changes as defined in the Javabean spec can now be annotated so that the engine register itself to listen for changes on fact properties. .
@propertyReactive Makes the type property reactive.

10.20. @key Attribute Functions

Declaring an attribute as a key attribute has 2 major effects on generated types:
  1. The attribute will be used as a key identifier for the type, and as so, the generated class will implement the equals() and hashCode() methods taking the attribute into account when comparing instances of this type.
  2. JBoss Rules will generate a constructor using all the key attributes as parameters.

10.21. @key Declaration Example

This is an example of @key declarations for a type. JBoss Rules will generate equals() and hashCode() methods that will check the firstName and lastName attributes to determine if two instances of Person are equal to each other. It will not check the age attribute. It will also generate a constructor taking firstName and lastName as parameters:
declare Person
    firstName : String @key
    lastName : String @key
    age : int

10.22. Creating an Instance with the Key Constructor Example

This is what creating an instance using the key constructor looks like:
Person person = new Person( "John", "Doe" );

10.23. Positional Arguments

Patterns support positional arguments on type declarations and are defined by the @position attribute.
Positional arguments are when you don't need to specify the field name, as the position maps to a known named field. (That is, Person( name == "mark" ) can be rewritten as Person( "mark"; ).) The semicolon ';' is important so that the engine knows that everything before it is a positional argument. You can mix positional and named arguments on a pattern by using the semicolon ';' to separate them. Any variables used in a positional that have not yet been bound will be bound to the field that maps to that position.

10.24. Positional Argument Example

Observe the example below:
declare Cheese
    name : String
    shop : String
    price : int
The default order is the declared order, but this can be overridden using @position
declare Cheese
    name : String @position(1)
    shop : String @position(2)
    price : int @position(0)

10.25. The @Position Annotation

The @Position annotation can be used to annotate original pojos on the classpath. Currently only fields on classes can be annotated. Inheritance of classes is supported, but not interfaces of methods.

10.26. Example Patterns

These example patterns have two constraints and a binding. The semicolon ';' is used to differentiate the positional section from the named argument section. Variables and literals and expressions using just literals are supported in positional arguments, but not variables:
Cheese( "stilton", "Cheese Shop", p; )
Cheese( "stilton", "Cheese Shop"; p : price )
Cheese( "stilton"; shop == "Cheese Shop", p : price )
Cheese( name == "stilton"; shop == "Cheese Shop", p : price )

Chapter 11. Additional Declarations

11.1. Declaring Metadata for Existing Types

JBoss Rules allows the declaration of metadata attributes for existing types in the same way as when declaring metadata attributes for new fact types. The only difference is that there are no fields in that declaration.

11.2. Declaring Metadata for Existing Types Example

This example shows how to declare metadata for an existing type:
import org.drools.examples.Person

declare Person
    @author( Bob )
    @dateOfCreation( 01-Feb-2009 )

11.3. Declaring Metadata Using a Fully Qualified Class Name Example

This example shows how you can declare metadata using the fully qualified class name instead of using the import annotation:
declare org.drools.examples.Person
    @author( Bob )
    @dateOfCreation( 01-Feb-2009 )

11.4. Parametrized Constructors for Declared Types Example

For a declared type like the following:
declare Person
    firstName : String @key
    lastName : String @key
    age : int
The compiler will implicitly generate 3 constructors: one without parameters, one with the @key fields and one with all fields.
Person() // parameterless constructor
Person( String firstName, String lastName )
Person( String firstName, String lastName, int age )

11.5. Non-Typesafe Classes

The @typesafe( <boolean>) annotation has been added to type declarations. By default all type declarations are compiled with type safety enabled. @typesafe( false ) provides a means to override this behaviour by permitting a fall-back, to type unsafe evaluation where all constraints are generated as MVEL constraints and executed dynamically. This is useful when dealing with collections that do not have any generics or mixed type collections.

11.6. Accessing Declared Types from the Application Code

Sometimes applications need to access and handle facts from the declared types. In such cases, JBoss Rules provides a simplified API for the most common fact handling the application wishes to do. A declared fact will belong to the package where it was declared.

11.7. Declaring a Type

This illustrates the process of declaring a type:
package org.drools.examples

import java.util.Date

declare Person
    name : String
    dateOfBirth : Date
    address : Address

11.8. Handling Declared Fact Types Through the API Example

This example illustrates the handling of declared fact types through the API:
// get a reference to a knowledge base with a declared type:
KnowledgeBase kbase = ...

// get the declared FactType
FactType personType = kbase.getFactType( "org.drools.examples",
                                         "Person" );

// handle the type as necessary:
// create instances:
Object bob = personType.newInstance();

// set attributes values
personType.set( bob,
                "Bob" );
personType.set( bob,
                42 );

// insert fact into a session
StatefulKnowledgeSession ksession = ...
ksession.insert( bob );

// read attributes
String name = personType.get( bob, "name" );
int age = personType.get( bob, "age" );

The API also includes other helpful methods, like setting all the attributes at once, reading values from a Map, or reading all attributes at once, into a Map.

11.9. Type Declaration Extends

Type declarations support the 'extends' keyword for inheritance. To extend a type declared in Java by a DRL declared subtype, repeat the supertype in a declare statement without any fields.

11.10. Type Declaration Extends Example

This illustrates the use of the extends annotation:
import org.people.Person

declare Person

declare Student extends Person
    school : String

declare LongTermStudent extends Student
    years : int
    course : String

11.11. Traits

Traits allow you to model multiple dynamic types which do not fit naturally in a class hierarchy. A trait is an interface that can be applied (and eventually removed) to an individual object at runtime. To create a trait out of an interface, a @format(trait) annotation is added to its declaration in DRL.

11.12. Traits Example

declare GoldenCustomer
    // fields will map to getters/setters
    code     : String
    balance  : long
    discount : int
    maxExpense : long
In order to apply a trait to an object, the new don keyword is added:
    $c : Customer()
    GoldenCustomer gc = don( $c, Customer.class );

11.13. Core Objects and Traits

When a core object dons a trait, a proxy class is created on the fly (one such class will be generated lazily for each core/trait class combination). The proxy instance, which wraps the core object and implements the trait interface, is inserted automatically and will possibly activate other rules. An immediate advantage of declaring and using interfaces, getting the implementation proxy for free from the engine, is that multiple inheritance hierarchies can be exploited when writing rules. The core classes, however, need not implement any of those interfaces statically, also facilitating the use of legacy classes as cores. Any object can don a trait. For efficiency reasons, however, you can add the @Traitable annotation to a declared bean class to reduce the amount of glue code that the compiler will have to generate. This is optional and will not change the behavior of the engine.

11.14. @Traitable Example

This illustrates the use of the @traitable annotation:
declare Customer
    code    : String
    balance : long

11.15. Writing Rules with Traits

The only connection between core classes and trait interfaces is at the proxy level. (That is, a trait is not specifically tied to a core class.) This means that the same trait can be applied to totally different objects. For this reason, the trait does not transparently expose the fields of its core object. When writing a rule using a trait interface, only the fields of the interface will be available, as usual. However, any field in the interface that corresponds to a core object field, will be mapped by the proxy class.

11.16. Rules with Traits Example

This example illustrates the trait interface being mapped to a field:
    $o: OrderItem( $p : price, $code : custCode )
    $c: GoldenCustomer( code == $code, $a : balance, $d: discount )
    $c.setBalance( $a - $p*$d );

11.17. Hidden Fields

Hidden fields are fields in the core class not exposed by the interface.

11.18. The Two-Part Proxy

The two-part proxy has been developed to deal with soft and hidden fields which are not processed intuitively. Internally, proxies are formed by a proper proxy and a wrapper. The former implements the interface, while the latter manages the core object fields, implementing a name/value map to supports soft fields. The proxy uses both the core object and the map wrapper to implement the interface, as needed.

11.19. Wrappers

The wrapper provides a looser form of typing when writing rules. However, it has also other uses. The wrapper is specific to the object it wraps, regardless of how many traits have been attached to an object. All the proxies on the same object will share the same wrapper. Additionally, the wrapper contains a back-reference to all proxies attached to the wrapped object, effectively allowing traits to see each other.

11.20. Wrapper Example

This is an example of using the wrapper:
    $sc : GoldenCustomer( $c : code, // hard getter
                          $maxExpense : maxExpense > 1000 // soft getter
    $sc.setDiscount( ... ); // soft setter

11.21. Wrapper with isA Annotation Example

This illustrates a wrapper in use with the isA annotation:
$sc : GoldenCustomer( $maxExpense : maxExpense > 1000,
                      this isA "SeniorCustomer"

11.22. Removing Traits

The business logic may require that a trait is removed from a wrapped object. There are two ways to do so:
Logical don
Results in a logical insertion of the proxy resulting from the traiting operation.
    don( $x, // core object
         Customer.class, // trait class
         true // optional flag for logical insertion
The shed keyword
The shed keyword causes the retraction of the proxy corresponding to the given argument type
    Thing t = shed( $x, GoldenCustomer.class )
This operation returns another proxy implementing the org.drools.factmodel.traits.Thing interface, where the getFields() and getCore() methods are defined. Internally, all declared traits are generated to extend this interface (in addition to any others specified). This allows to preserve the wrapper with the soft fields which would otherwise be lost.

11.23. Rule Syntax Example

This is an example of the syntax you should use when creating a rule:
rule "<name>"
    <conditional element>*

11.24. Rule Attributes

Table 11.1. Rule Attributes

Attribute Name Default Value Type Description
When a rule's consequence modifies a fact it may cause the rule to activate again, causing an infinite loop. Setting no-loop to true will skip the creation of another Activation for the rule with the current set of facts.
Ruleflow is a Drools feature that lets you exercise control over the firing of rules. Rules that are assembled by the same ruleflow-group identifier fire only when their group is active.
Whenever a ruleflow-group becomes active or an agenda-group receives the focus, any rule within that group that has lock-on-active set to true will not be activated any more; irrespective of the origin of the update, the activation of a matching rule is discarded. This is a stronger version of no-loop, because the change could now be caused not only by the rule itself. It's ideal for calculation rules where you have a number of rules that modify a fact and you don't want any rule re-matching and firing again. Only when the ruleflow-group is no longer active or the agenda-group loses the focus those rules with lock-on-active set to true become eligible again for their activations to be placed onto the agenda.
Each rule has an integer salience attribute which defaults to zero and can be negative or positive. Salience is a form of priority where rules with higher salience values are given higher priority when ordered in the Activation queue.
Agenda groups allow the user to partition the Agenda providing more execution control. Only rules in the agenda group that has acquired the focus are allowed to fire.
When a rule is activated where the auto-focus value is true and the rule's agenda group does not have focus yet, then it is given focus, allowing the rule to potentially fire.
Rules that belong to the same activation-group, identified by this attribute's string value, will only fire exclusively. In other words, the first rule in an activation-group to fire will cancel the other rules' activations, i.e., stop them from firing.
As specified by the package
The dialect species the language to be used for any code expressions in the LHS or the RHS code block. Currently two dialects are available, Java and MVEL. While the dialect can be specified at the package level, this attribute allows the package definition to be overridden for a rule.
String, containing a date and time definition
A rule can only activate if the current date and time is after date-effective attribute.
String, containing a date and time definition
A rule cannot activate if the current date and time is after the date-expires attribute.
no default value
The duration dictates that the rule will fire after a specified duration, if it is still true.

11.25. Rule Attribute Example

This is an example for using a rule attribute:
rule "my rule"
    salience 42
    agenda-group "number-1"
     when ...

11.26. Timer Attribute Example

This is what the timer attribute looks like:
timer ( int: <initial delay> <repeat interval>? )
timer ( int: 30s )
timer ( int: 30s 5m )

timer ( cron: <cron expression> )
timer ( cron:* 0/15 * * * ? )

11.27. Timers

The following timers are available in JBoss Rules:
Interval (indicated by "int:") timers follow the semantics of java.util.Timer objects, with an initial delay and an optional repeat interval.
Cron (indicated by "cron:") timers follow standard Unix cron expressions.

11.28. Cron Timer Example

This is what the Cron timer looks like:
rule "Send SMS every 15 minutes"
    timer (cron:* 0/15 * * * ?)
    $a : Alarm( on == true )
    channels[ "sms" ].insert( new Sms( $a.mobileNumber, "The alarm is still on" );

11.29. Calendars

Calendars are used to control when rules can fire. JBoss Rules uses the Quartz calendar.

11.30. Quartz Calendar Example

This is what the Quartz calendar looks like:
Calendar weekDayCal = QuartzHelper.quartzCalendarAdapter(org.quartz.Calendar quartzCal)

11.31. Registering a Calendar

Procedure 11.1. Task

  1. Start a StatefulKnowledgeSession.
  2. Use the following code to register the calendar:
    ksession.getCalendars().set( "weekday", weekDayCal );
  3. If you wish to utilize the calendar and a timer together, use the following code:
    rule "weekdays are high priority"
       calendars "weekday"
       timer (int:0 1h)
        send( "priority high - we have an alarm” );
    rule "weekend are low priority"
       calendars "weekend"
       timer (int:0 4h)
        send( "priority low - we have an alarm” );

11.32. Left Hand Side

The Left Hand Side (LHS) is a common name for the conditional part of the rule. It consists of zero or more Conditional Elements. If the LHS is empty, it will be considered as a condition element that is always true and it will be activated once, when a new WorkingMemory session is created.

11.33. Conditional Elements

Conditional elements work on one or more patterns. The most common conditional element is and. It is implicit when you have multiple patterns in the LHS of a rule that is not connected in any way.

11.34. Rule Without a Conditional Element Example

This is what a rule without a conditional element looks like:
rule "no CEs"
    // empty
    ... // actions (executed once)

// The above rule is internally rewritten as:

rule "eval(true)"
    eval( true )
    ... // actions (executed once)

Chapter 12. Patterns

12.1. Patterns

A pattern element is the most important Conditional Element. It can potentially match on each fact that is inserted in the working memory. A pattern contains constraints and has an optional pattern binding.

12.2. Pattern Example

This is what a pattern looks like:
rule "2 unconnected patterns"
    ... // actions

// The above rule is internally rewritten as:

rule "2 and connected patterns"
    and Pattern2()
    ... // actions


An and cannot have a leading declaration binding. This is because a declaration can only reference a single fact at a time, and when the and is satisfied it matches both facts.

12.3. Pattern Matching

A pattern matches against a fact of the given type. The type need not be the actual class of some fact object. Patterns may refer to superclasses or even interfaces, thereby potentially matching facts from many different classes. The constraints are defined inside parentheses.

12.4. Pattern Binding

Patterns can be bound to a matching object. This is accomplished using a pattern binding variable such as $p.

12.5. Pattern Binding with Variable Example

This is what pattern binding using a variable looks like:
rule ...
    $p : Person()
    System.out.println( "Person " + $p );


The prefixed dollar symbol ($) is not mandatory.

12.6. Constraints

A constraint is an expression that returns true or false. For example, you can have a constraint that states five is smaller than six.

Chapter 13. Elements and Variables

13.1. Property Access on Java Beans (POJOs)

Any bean property can be used directly. A bean property is exposed using a standard Java bean getter: a method getMyProperty() (or isMyProperty() for a primitive boolean) which takes no arguments and return something.
JBoss Rules uses the standard JDK Introspector class to do this mapping, so it follows the standard Java bean specification.


Property accessors must not change the state of the object in a way that may effect the rules. The rule engine effectively caches the results of its matching in between invocations to make it faster.

13.2. POJO Example

This is what the bean property looks like:
Person( age == 50 )

// this is the same as:
Person( getAge() == 50 )
The age property
The age property is written as age in DRL instead of the getter getAge()
Property accessors
You can use property access (age) instead of getters explicitly (getAge()) because of performance enhancements through field indexing.

13.3. Working with POJOs

Procedure 13.1. Task

  1. Observe the example below:
    public int getAge() {
        Date now = DateUtil.now(); // Do NOT do this
        return DateUtil.differenceInYears(now, birthday);
  2. To solve this, insert a fact that wraps the current date into working memory and update that fact between fireAllRules as needed.

13.4. POJO Fallbacks

When working with POJOs, a fallback method is applied. If the getter of a property cannot be found, the compiler will resort to using the property name as a method name and without arguments. Nested properties are also indexed.

13.5. Fallback Example

This is what happens when a fallback is implemented:
Person( age == 50 )

// If Person.getAge() does not exists, this falls back to:
Person( age() == 50 )
This is what it looks like as a nested property:
Person( address.houseNumber == 50 )

// this is the same as:
Person( getAddress().getHouseNumber() == 50 )


In a stateful session, care should be taken when using nested accessors as the Working Memory is not aware of any of the nested values and does not know when they change. Consider them immutable while any of their parent references are inserted into the Working Memory. If you wish to modify a nested value you should mark all of the outer facts as updated. In the above example, when the houseNumber changes, any Person with that Address must be marked as updated.

13.6. Java Expressions

Table 13.1. Java Expressions

Capability Example
You can use any Java expression that returns a boolean as a constraint inside the parentheses of a pattern. Java expressions can be mixed with other expression enhancements, such as property access.
Person( age == 50 )
You can change the evaluation priority by using parentheses, as in any logic or mathematical expression.
Person( age > 100 && ( age % 10 == 0 ) )
You can reuse Java methods.
Person( Math.round( weight / ( height * height ) ) < 25.0 )
Type coercion is always attempted if the field and the value are of different types; exceptions will be thrown if a bad coercion is attempted.
Person( age == "10" ) // "10" is coerced to 10


Methods must not change the state of the object in a way that may affect the rules. Any method executed on a fact in the LHS should be a read only method.


The state of a fact should not change between rule invocations (unless those facts are marked as updated to the working memory on every change):
Person( System.currentTimeMillis() % 1000 == 0 ) // Do NOT do this


All operators have normal Java semantics except for == and !=.
The == operator has null-safe equals() semantics:
// Similar to: java.util.Objects.equals(person.getFirstName(), "John")
// so (because "John" is not null) similar to:
// "John".equals(person.getFirstName())
Person( firstName == "John" )
The != operator has null-safe !equals() semantics:
// Similar to: !java.util.Objects.equals(person.getFirstName(), "John")
Person( firstName != "John" )

13.7. Comma-Separated Operators

The comma character (',') is used to separate constraint groups. It has implicit and connective semantics.
The comma operator is used at the top level constraint as it makes them easier to read and the engine will be able to optimize them.

13.8. Comma-Separated Operator Example

The following illustrates comma-separated scenarios in implicit and connective semantics:
// Person is at least 50 and weighs at least 80 kg
Person( age > 50, weight > 80 )
// Person is at least 50, weighs at least 80 kg and is taller than 2 meter.
Person( age > 50, weight > 80, height > 2 )


The comma (,) operator cannot be embedded in a composite constraint expression, such as parentheses.

13.9. Binding Variables

You can bind properties to variables in JBoss Rules. It allows for faster execution and performance.

13.10. Binding Variable Examples

This is an example of a property bound to a variable:
// 2 persons of the same age
Person( $firstAge : age ) // binding
Person( age == $firstAge ) // constraint expression


For backwards compatibility reasons, it's allowed (but not recommended) to mix a constraint binding and constraint expressions as such:
// Not recommended
Person( $age : age * 2 < 100 )
// Recommended (separates bindings and constraint expressions)
Person( age * 2 < 100, $age : age )

13.11. Unification

You can unify arguments across several properties. While positional arguments are always processed with unification, the unification symbol, ':=', exists for named arguments.

13.12. Unification Example

This is what unifying two arguments looks like:
Person( $age := age ) 
Person( $age := age)

13.13. Options and Operators in JBoss Rules

Table 13.2. Options and Operators in JBoss Rules

Option Description Example
Date literal
The date format dd-mmm-yyyy is supported by default. You can customize this by providing an alternative date format mask as the System property named drools.dateformat. If more control is required, use a restriction.
Cheese( bestBefore < "27-Oct-2009" )
List and Map access
You can directly access a List value by index.
// Same as childList(0).getAge() == 18
Person( childList[0].age == 18 )
Value key
You can directly access a Map value by key.
// Same as credentialMap.get("jsmith").isValid()
Person( credentialMap["jsmith"].valid )
Abbreviated combined relation condition
This allows you to place more than one restriction on a field using the restriction connectives && or ||. Grouping via parentheses is permitted, resulting in a recursive syntax pattern.
// Simple abbreviated combined relation condition using a single &&
Person( age > 30 && < 40 )
// Complex abbreviated combined relation using groupings
Person( age ( (> 30 && < 40) ||
              (> 20 && < 25) ) )
// Mixing abbreviated combined relation with constraint connectives
Person( age > 30 && < 40 || location == "london" )
Operators can be used on properties with natural ordering. For example, for Date fields, < means before, for String fields, it means alphabetically lower.
Person( firstName < $otherFirstName )
Person( birthDate < $otherBirthDate )
Operator matches
Matches a field against any valid Java regular expression. Typically that regexp is a string literal, but variables that resolve to a valid regexp are also allowed. It only applies on String properties. Using matches against a null value always evaluates to false.
Cheese( type matches "(Buffalo)?\\S*Mozarella" )
Operator not matches
The operator returns true if the String does not match the regular expression. The same rules apply as for the matches operator. It only applies on String properties.
Cheese( type not matches "(Buffulo)?\\S*Mozarella" )
The operator contains
The operator contains is used to check whether a field that is a Collection or array contains the specified value. It only applies on Collection properties.
CheeseCounter( cheeses contains "stilton" ) // contains with a String literal
CheeseCounter( cheeses contains $var ) // contains with a variable
The operator not contains
The operator not contains is used to check whether a field that is a Collection or array does not contain the specified value. It only applies on Collection properties.
CheeseCounter( cheeses not contains "cheddar" ) // not contains with a String literal
CheeseCounter( cheeses not contains $var ) // not contains with a variable
The operator memberOf
The operator memberOf is used to check whether a field is a member of a collection or array; that collection must be a variable.
CheeseCounter( cheese memberOf $matureCheeses )
The operator not memberOf
The operator not memberOf is used to check whether a field is not a member of a collection or array. That collection must be a variable.
CheeseCounter( cheese not memberOf $matureCheeses )
The operator soundslike
This operator is similar to matches, but it checks whether a word has almost the same sound (using English pronunciation) as the given value.
// match cheese "fubar" or "foobar"
Cheese( name soundslike 'foobar' )
The operator str
The operator str is used to check whether a field that is a String starts with or ends with a certain value. It can also be used to check the length of the String.
Message( routingValue str[startsWith] "R1" )
Message( routingValue str[endsWith] "R2" )
Message( routingValue str[length] 17 )
Compound Value Restriction
Compound value restriction is used where there is more than one possible value to match. Currently only the in and not in evaluators support this. The second operand of this operator must be a comma-separated list of values, enclosed in parentheses. Values may be given as variables, literals, return values or qualified identifiers. Both evaluators are actually syntactic sugar, internally rewritten as a list of multiple restrictions using the operators != and ==.
Person( $cheese : favouriteCheese )
Cheese( type in ( "stilton", "cheddar", $cheese ) )
Inline Eval Operator (deprecated)
An inline eval constraint can use any valid dialect expression as long as it results to a primitive boolean. The expression must be constant over time. Any previously bound variable, from the current or previous pattern, can be used; autovivification is also used to auto-create field binding variables. When an identifier is found that is not a current variable, the builder looks to see if the identifier is a field on the current object type, if it is, the field binding is auto-created as a variable of the same name. This is called autovivification of field variables inside of inline eval's.
Person( girlAge : age, sex = "F" )
Person( eval( age == girlAge + 2 ), sex = 'M' ) // eval() is actually obsolete in this example

13.14. Operator Precedence

Table 13.3. Operator precedence

Operator type Operators Notes
(nested) property access . Not normal Java semantics
List/Map access [ ] Not normal Java semantics
constraint binding : Not normal Java semantics
multiplicative * /%
additive + -
shift << >>>>>
relational < ><= >=instanceof
equality == != Does not use normal Java (not) same semantics: uses (not) equals semantics instead.
non-short circuiting AND &
non-short circuiting exclusive OR ^
non-short circuiting inclusive OR |
logical AND &&
logical OR ||
ternary ? :
Comma separated AND , Not normal Java semantics

13.15. Fine Grained Property Change Listeners

This feature allows the pattern matching to only react to modification of properties actually constrained or bound inside of a given pattern. This helps with performance and recursion and avoid artificial object splitting.


By default this feature is off in order to make the behavior of the rule engine backward compatible with the former releases. When you want to activate it on a specific bean you have to annotate it with @propertyReactive.

13.16. Fine Grained Property Change Listener Example

DRL example
declare Person
          firstName : String
          lastName : String
Java class example
          public static class Person {
          private String firstName;
          private String lastName;

13.17. Working with Fine Grained Property Change Listeners

Using these listeners means you do not need to implement the no-loop attribute to avoid an infinite recursion. The engine recognizes that the pattern matching is done on the property while the RHS of the rule modifies other the properties. On Java classes, you can also annotate any method to say that its invocation actually modifies other properties.

13.18. Using Patterns with @watch

Annotating a pattern with @watch allows you to modify the inferred set of properties for which that pattern will react. The properties named in the @watch annotation are added to the ones automatically inferred. You can explicitly exclude one or more of them by beginning their name with a ! and to make the pattern to listen for all or none of the properties of the type used in the pattern respectively with the wildcards * and !*.

13.19. @watch Example

This is the @watch annotation in a rule's LHS:
// listens for changes on both firstName (inferred) and lastName
          Person( firstName == $expectedFirstName ) @watch( lastName )

          // listens for all the properties of the Person bean
          Person( firstName == $expectedFirstName ) @watch( * )

          // listens for changes on lastName and explicitly exclude firstName
          Person( firstName == $expectedFirstName ) @watch( lastName, !firstName )

          // listens for changes on all the properties except the age one
          Person( firstName == $expectedFirstName ) @watch( *, !age )


Since doesn't make sense to use this annotation on a pattern using a type not annotated with @PropertyReactive the rule compiler will raise a compilation error if you try to do so. Also the duplicated usage of the same property in @watch (for example like in: @watch( firstName, ! firstName ) ) will end up in a compilation error.

13.20. Using @PropertySpecificOption

You can enable @watch by default or completely disallow it using the on option of the KnowledgeBuilderConfiguration. This new PropertySpecificOption can have one of the following 3 values:
- DISABLED => the feature is turned off and all the other related annotations are just ignored
          - ALLOWED => this is the default behavior: types are not property reactive unless they are not annotated with @PropertySpecific
          - ALWAYS => all types are property reactive by default

13.21. Basic Conditional Elements

Table 13.4. Basic Conditional Elements

Name Description Example Additional options
The Conditional Element and is used to group other Conditional Elements into a logical conjunction. JBoss Rules supports both prefix and and infix and. It supports explicit grouping with parentheses. You can also use traditional infix and prefix and.
Cheese( cheeseType : type ) and Person( favouriteCheese == cheeseType )
//infixAnd with grouping
( Cheese( cheeseType : type ) and
  ( Person( favouriteCheese == cheeseType ) or 
    Person( favouriteCheese == cheeseType ) )
Prefix and is also supported:
(and Cheese( cheeseType : type )
     Person( favouriteCheese == cheeseType ) )
The root element of the LHS is an implicit prefix and and doesn't need to be specified:
    Cheese( cheeseType : type )
    Person( favouriteCheese == cheeseType )
This is a shortcut for generating two or more similar rules. JBoss Rules supports both prefix or and infix or. You can use traditional infix, prefix and explicit grouping parentheses.
Cheese( cheeseType : type ) or Person( favouriteCheese == cheeseType )
//infixOr with grouping
( Cheese( cheeseType : type ) or
  ( Person( favouriteCheese == cheeseType ) and
    Person( favouriteCheese == cheeseType ) )
(or Person( sex == "f", age > 60 )
    Person( sex == "m", age > 65 )
Allows for optional pattern binding. Each pattern must be bound separately, using eponymous variables:
pensioner : ( Person( sex == "f", age > 60 ) or Person( sex == "m", age > 65 ) )
(or pensioner : Person( sex == "f", age > 60 ) 
    pensioner : Person( sex == "m", age > 65 ) )
This checks to ensure an object specified as absent is not included in the Working Memory. It may be followed by parentheses around the condition elements it applies to. (In a single pattern you can omit the parentheses.)
// Brackets are optional:
not Bus(color == "red")
// Brackets are optional:
not ( Bus(color == "red", number == 42) )
// "not" with nested infix and - two patterns,
// brackets are requires:
not ( Bus(color == "red") and
      Bus(color == "blue") )
This checks the working memory to see if a specified item exists. The keyword exists must be followed by parentheses around the CEs that it applies to. (In a single pattern you can omit the parentheses.)
exists Bus(color == "red")
// brackets are optional:
exists ( Bus(color == "red", number == 42) )
// "exists" with nested infix and,
// brackets are required:
exists ( Bus(color == "red") and
         Bus(color == "blue") )


The behavior of the Conditional Element or is different from the connective || for constraints and restrictions in field constraints. The engine cannot interpret the Conditional Element or. Instead, a rule with or is rewritten as a number of subrules. This process ultimately results in a rule that has a single or as the root node and one subrule for each of its CEs. Each subrule can activate and fire like any normal rule; there is no special behavior or interaction between these subrules.

13.22. The Conditional Element Forall

This element evaluates to true when all facts that match the first pattern match all the remaining patterns. It is a scope delimiter. Therefore, it can use any previously bound variable, but no variable bound inside it will be available for use outside of it.
Forall can be nested inside other CEs. For instance, forall can be used inside a not CE. Only single patterns have optional parentheses, so with a nested forall parentheses must be used.

13.23. Forall Examples

Evaluating to true
rule "All English buses are red"
    forall( $bus : Bus( type == 'english') 
                   Bus( this == $bus, color = 'red' ) )
    // all English buses are red
Single pattern forall
rule "All Buses are Red"
    forall( Bus( color == 'red' ) )
    // all Bus facts are red
Multi-pattern forall
rule "all employees have health and dental care programs"
    forall( $emp : Employee()
            HealthCare( employee == $emp )
            DentalCare( employee == $emp )
    // all employees have health and dental care
Nested forall
rule "not all employees have health and dental care"
    not ( forall( $emp : Employee()
                  HealthCare( employee == $emp )
                  DentalCare( employee == $emp ) ) 
    // not all employees have health and dental care

13.24. The Conditional Element From

The Conditional Element from enables users to specify an arbitrary source for data to be matched by LHS patterns. This allows the engine to reason over data not in the Working Memory. The data source could be a sub-field on a bound variable or the results of a method call. It is a powerful construction that allows out of the box integration with other application components and frameworks. One common example is the integration with data retrieved on-demand from databases using hibernate named queries.
The expression used to define the object source is any expression that follows regular MVEL syntax. Therefore, it allows you to easily use object property navigation, execute method calls and access maps and collections elements.


Using from with lock-on-active rule attribute can result in rules not being fired.
There are several ways to address this issue:
  • Avoid the use of from when you can assert all facts into working memory or use nested object references in your constraint expressions (shown below).
  • Place the variable assigned used in the modify block as the last sentence in your condition (LHS).
  • Avoid the use of lock-on-active when you can explicitly manage how rules within the same rule-flow group place activations on one another.

13.25. From Examples

Reasoning and binding on patterns
rule "validate zipcode"
    Person( $personAddress : address ) 
    Address( zipcode == "23920W") from $personAddress 
    // zip code is ok
Using a graph notation
rule "validate zipcode"
    $p : Person( ) 
    $a : Address( zipcode == "23920W") from $p.address 
    // zip code is ok
Iterating over all objects
rule "apply 10% discount to all items over US$ 100,00 in an order"
    $order : Order()
    $item  : OrderItem( value > 100 ) from $order.items
    // apply discount to $item
Use with lock-on-active
rule "Assign people in North Carolina (NC) to sales region 1"
ruleflow-group "test"
lock-on-active true
    $p : Person(address.state == "NC" )  
    modify ($p) {} // Assign person to sales region 1 in a modify block

rule "Apply a discount to people in the city of Raleigh"
ruleflow-group "test"
lock-on-active true
    $p : Person(address.city == "Raleigh" )  
    modify ($p) {} //Apply discount to person in a modify block

13.26. The Conditional Element Collect

The Conditional Element collect allows rules to reason over a collection of objects obtained from the given source or from the working memory. In First Oder Logic terms this is the cardinality quantifier.
The result pattern of collect can be any concrete class that implements the java.util.Collection interface and provides a default no-arg public constructor. You can use Java collections like ArrayList, LinkedList and HashSet or your own class, as long as it implements the java.util.Collection interface and provide a default no-arg public constructor.
Variables bound before the collect CE are in the scope of both source and result patterns and therefore you can use them to constrain both your source and result patterns. Any binding made inside collect is not available for use outside of it.

13.27. The Conditional Element Accumulate

The Conditional Element accumulate is a more flexible and powerful form of collect, in the sense that it can be used to do what collect does and also achieve results that the CE collect is not capable of doing. It allows a rule to iterate over a collection of objects, executing custom actions for each of the elements. At the end it returns a result object.
Accumulate supports both the use of pre-defined accumulate functions, or the use of inline custom code. Inline custom code should be avoided though, as it is harder for rule authors to maintain, and frequently leads to code duplication. Accumulate functions are easier to test and reuse.
The Accumulate CE also supports multiple different syntaxes. The preferred syntax is the top level accumulate, as noted bellow, but all other syntaxes are supported for backward compatibility.

13.28. Syntax for the Conditional Element Accumulate

Top level accumulate syntax
accumulate( <source pattern>; <functions> [;<constraints>] )
Syntax example
rule "Raise alarm"
    $s : Sensor()
    accumulate( Reading( sensor == $s, $temp : temperature );
                $min : min( $temp ),
                $max : max( $temp ),
                $avg : average( $temp );
                $min < 20, $avg > 70 )
    // raise the alarm
In the above example, min, max and average are Accumulate Functions and will calculate the minimum, maximum and average temperature values over all the readings for each sensor.

13.29. Functions of the Conditional Element Accumulate

  • average
  • min
  • max
  • count
  • sum
  • collectList
  • collectSet
These common functions accept any expression as input. For instance, if someone wants to calculate the average profit on all items of an order, a rule could be written using the average function:
rule "Average profit"
    $order : Order()
    accumulate( OrderItem( order == $order, $cost : cost, $price : price );
                $avgProfit : average( 1 - $cost / $price ) )
    // average profit for $order is $avgProfit

13.30. The Conditional Element accumulate and Pluggability

Accumulate functions are all pluggable. That means that if needed, custom, domain specific functions can easily be added to the engine and rules can start to use them without any restrictions. To implement a new Accumulate Function all one needs to do is to create a Java class that implements the org.drools.runtime.rule.TypedAccumulateFunction interface and add a line to the configuration file or set a system property to let the engine know about the new function.

13.31. The Conditional Element accumulate and Pluggability Example

As an example of an Accumulate Function implementation, the following is the implementation of the average function:
 * An implementation of an accumulator capable of calculating average values
public class AverageAccumulateFunction implements org.drools.runtime.rule.TypedAccumulateFunction {

    public void readExternal(ObjectInput in) throws IOException, ClassNotFoundException {


    public void writeExternal(ObjectOutput out) throws IOException {


    public static class AverageData implements Externalizable {
        public int    count = 0;
        public double total = 0;
        public AverageData() {}

        public void readExternal(ObjectInput in) throws IOException, ClassNotFoundException {
            count   = in.readInt();
            total   = in.readDouble();

        public void writeExternal(ObjectOutput out) throws IOException {


    /* (non-Javadoc)
     * @see org.drools.base.accumulators.AccumulateFunction#createContext()
    public Serializable createContext() {
        return new AverageData();

    /* (non-Javadoc)
     * @see org.drools.base.accumulators.AccumulateFunction#init(java.lang.Object)
    public void init(Serializable context) throws Exception {
        AverageData data = (AverageData) context;
        data.count = 0;
        data.total = 0;

    /* (non-Javadoc)
     * @see org.drools.base.accumulators.AccumulateFunction#accumulate(java.lang.Object, java.lang.Object)
    public void accumulate(Serializable context,
                           Object value) {
        AverageData data = (AverageData) context;
        data.total += ((Number) value).doubleValue();

    /* (non-Javadoc)
     * @see org.drools.base.accumulators.AccumulateFunction#reverse(java.lang.Object, java.lang.Object)
    public void reverse(Serializable context,
                        Object value) throws Exception {
        AverageData data = (AverageData) context;
        data.total -= ((Number) value).doubleValue();

    /* (non-Javadoc)
     * @see org.drools.base.accumulators.AccumulateFunction#getResult(java.lang.Object)
    public Object getResult(Serializable context) throws Exception {
        AverageData data = (AverageData) context;
        return new Double( data.count == 0 ? 0 : data.total / data.count );

    /* (non-Javadoc)
     * @see org.drools.base.accumulators.AccumulateFunction#supportsReverse()
    public boolean supportsReverse() {
        return true;

     * {@inheritDoc}
    public Class< ? > getResultType() {
        return Number.class;


13.32. Code for the Conditional Element Accumulate's Functions

Code for plugging in functions (to be entered into the config file)
jbossrules.accumulate.function.average =
Alternate Syntax: single function with return type
rule "Apply 10% discount to orders over US$ 100,00"
    $order : Order()
    $total : Number( doubleValue > 100 ) 
             from accumulate( OrderItem( order == $order, $value : value ),
                              sum( $value ) )
    # apply discount to $order
** item name **
** item description **

13.33. Accumulate with Inline Custom Code


The use of accumulate with inline custom code is not a good practice for several reasons, including difficulties on maintaining and testing rules that use them, as well as the inability of reusing that code. Implementing your own accumulate functions allows for simpler testing. This form of accumulate is supported for backward compatibility only.
The general syntax of the accumulate CE with inline custom code is:
<result pattern> from accumulate( <source pattern>,
                                  init( <init code> ),
                                  action( <action code> ),
                                  reverse( <reverse code> ),
                                  result( <result expression> ) )
The meaning of each of the elements is the following:
  • <source pattern>: the source pattern is a regular pattern that the engine will try to match against each of the source objects.
  • <init code>: this is a semantic block of code in the selected dialect that will be executed once for each tuple, before iterating over the source objects.
  • <action code>: this is a semantic block of code in the selected dialect that will be executed for each of the source objects.
  • <reverse code>: this is an optional semantic block of code in the selected dialect that if present will be executed for each source object that no longer matches the source pattern. The objective of this code block is to undo any calculation done in the <action code> block, so that the engine can do decremental calculation when a source object is modified or retracted, hugely improving performance of these operations.
  • <result expression>: this is a semantic expression in the selected dialect that is executed after all source objects are iterated.
  • <result pattern>: this is a regular pattern that the engine tries to match against the object returned from the <result expression>. If it matches, the accumulate conditional element evaluates to true and the engine proceeds with the evaluation of the next CE in the rule. If it does not matches, the accumulate CE evaluates to false and the engine stops evaluating CEs for that rule.

13.34. Accumulate with Inline Custom Code Examples

Inline custom code
rule "Apply 10% discount to orders over US$ 100,00"
    $order : Order()
    $total : Number( doubleValue > 100 ) 
             from accumulate( OrderItem( order == $order, $value : value ),
                              init( double total = 0; ),
                              action( total += $value; ),
                              reverse( total -= $value; ),
                              result( total ) )
    # apply discount to $order
In the above example, for each Order in the Working Memory, the engine will execute the init code initializing the total variable to zero. Then it will iterate over all OrderItem objects for that order, executing the action for each one (in the example, it will sum the value of all items into the total variable). After iterating over all OrderItem objects, it will return the value corresponding to the result expression (in the above example, the value of variable total). Finally, the engine will try to match the result with the Number pattern, and if the double value is greater than 100, the rule will fire.
Instantiating and populating a custom object
rule "Accumulate using custom objects"
    $person   : Person( $likes : likes )
    $cheesery : Cheesery( totalAmount > 100 )
                from accumulate( $cheese : Cheese( type == $likes ),
                                 init( Cheesery cheesery = new Cheesery(); ),
                                 action( cheesery.addCheese( $cheese ); ),
                                 reverse( cheesery.removeCheese( $cheese ); ),
                                 result( cheesery ) );
    // do something

13.35. Conditional Element Eval

The conditional element eval is essentially a catch-all which allows any semantic code (that returns a primitive boolean) to be executed. This code can refer to variables that were bound in the LHS of the rule, and functions in the rule package. Overuse of eval reduces the declarativeness of your rules and can result in a poorly performing engine. While eval can be used anywhere in the patterns, the best practice is to add it as the last conditional element in the LHS of a rule.
Evals cannot be indexed and thus are not as efficient as Field Constraints. However this makes them ideal for being used when functions return values that change over time, which is not allowed within Field Constraints.

13.36. Conditional Element Eval Examples

This is what eval looks like in use:
p1 : Parameter()
p2 : Parameter()
eval( p1.getList().containsKey( p2.getItem() ) )
p1 : Parameter()
p2 : Parameter()
// call function isValid in the LHS
eval( isValid( p1, p2 ) )

13.37. The Right Hand Side

The Right Hand Side (RHS) is a common name for the consequence or action part of the rule. The main purpose of the RHS is to insert, retractor modify working memory data. It should contain a list of actions to be executed. The RHS part of a rule should also be kept small, thus keeping it declarative and readable.


If you find you need imperative and/or conditional code in the RHS, break the rule down into multiple rules.

13.38. RHS Convenience Methods

Table 13.5. RHS Convenience Methods

Name Description
update(object, handle);
Tells the engine that an object has changed (one that has been bound to something on the LHS) and rules that need to be reconsidered.
Using update(), the Knowledge Helper will look up the facthandle via an identity check for the passed object. (If you provide Property Change Listeners to your Java beans that you are inserting into the engine, you can avoid the need to call update() when the object changes.). After a fact's field values have changed you must call update before changing another fact, or you will cause problems with the indexing within the rule engine. The modify keyword avoids this problem.
Places a new object of your creation into the Working Memory.
Similar to insert, but the object will be automatically retracted when there are no more facts to support the truth of the currently firing rule.
Removes an object from Working Memory.

13.39. Convenience Methods using the Drools Variable

  • The call drools.halt() terminates rule execution immediately. This is required for returning control to the point whence the current session was put to work with fireUntilHalt().
  • Methods insert(Object o), update(Object o) and retract(Object o) can be called on drools as well, but due to their frequent use they can be called without the object reference.
  • drools.getWorkingMemory() returns the WorkingMemory object.
  • drools.setFocus( String s) sets the focus to the specified agenda group.
  • drools.getRule().getName(), called from a rule's RHS, returns the name of the rule.
  • drools.getTuple() returns the Tuple that matches the currently executing rule, and drools.getActivation() delivers the corresponding Activation. (These calls are useful for logging and debugging purposes.)

13.40. Convenience Methods using the Kcontext Variable

  • The call kcontext.getKnowledgeRuntime().halt() terminates rule execution immediately.
  • The accessor getAgenda() returns a reference to the session's Agenda, which in turn provides access to the various rule groups: activation groups, agenda groups, and rule flow groups. A fairly common paradigm is the activation of some agenda group, which could be done with the lengthy call:
    // give focus to the agenda group CleanUp
    kcontext.getKnowledgeRuntime().getAgenda().getAgendaGroup( "CleanUp" ).setFocus();
    (You can achieve the same using drools.setFocus( "CleanUp" ).)
  • To run a query, you call getQueryResults(String query), whereupon you may process the results.
  • A set of methods dealing with event management lets you add and remove event listeners for the Working Memory and the Agenda.
  • MethodgetKnowledgeBase() returns the KnowledgeBase object, the backbone of all the Knowledge in your system, and the originator of the current session.
  • You can manage globals with setGlobal(...), getGlobal(...) and getGlobals().
  • Method getEnvironment() returns the runtime's Environment.

13.41. The Modify Statement

Table 13.6. The Modify Statement

Name Description Syntax Example
This provides a structured approach to fact updates. It combines the update operation with a number of setter calls to change the object's fields.
modify ( <fact-expression> ) {
    <expression> [ , <expression> ]*
The parenthesized <fact-expression> must yield a fact object reference. The expression list in the block should consist of setter calls for the given object, to be written without the usual object reference, which is automatically prepended by the compiler.
rule "modify stilton"
    $stilton : Cheese(type == "stilton")
    modify( $stilton ){
        setPrice( 20 ),
        setAge( "overripe" )

13.42. Query Examples


To return the results use ksession.getQueryResults("name"), where "name" is the query's name. This returns a list of query results, which allow you to retrieve the objects that matched the query.
Query for people over the age of 30
query "people over the age of 30" 
    person : Person( age > 30 )
Query for people over the age of X, and who live in Y
query "people over the age of x"  (int x, String y)
    person : Person( age > x, location == y )

13.43. QueryResults Example

We iterate over the returned QueryResults using a standard "for" loop. Each element is a QueryResultsRow which we can use to access each of the columns in the tuple. These columns can be accessed by bound declaration name or index position:
QueryResults results = ksession.getQueryResults( "people over the age of 30" );
System.out.println( "we have " + results.size() + " people over the age  of 30" );

System.out.println( "These people are are over 30:" );

for ( QueryResultsRow row : results ) {
    Person person = ( Person ) row.get( "person" );
    System.out.println( person.getName() + "\n" );

13.44. Queries Calling Other Queries

Queries can call other queries. This combined with optional query arguments provides derivation query style backward chaining. Positional and named syntax is supported for arguments. It is also possible to mix both positional and named, but positional must come first, separated by a semi colon. Literal expressions can be passed as query arguments, but you cannot mix expressions with variables.


Using the '?' symbol in this process means the query is pull only and once the results are returned you will not receive further results as the underlying data changes.

13.45. Queries Calling Other Queries Example

Query calling another query
declare Location
    thing : String 
    location : String 

query isContainedIn( String x, String y ) 
    Location(x, y;)
    ( Location(z, y;) and ?isContainedIn(x, z;) )
Using live queries to reactively receive changes over time from query results
query isContainedIn( String x, String y ) 
    Location(x, y;)
    ( Location(z, y;) and isContainedIn(x, z;) )

rule look when 
    Person( $l : likes ) 
    isContainedIn( $l, 'office'; )
   insertLogical( $l 'is in the office' );

13.46. Unification for Derivation Queries

JBoss Rules supports unification for derivation queries. This means that arguments are optional. It is possible to call queries from Java leaving arguments unspecified using the static field org.drools.runtime.rule.Variable.v. (You must use 'v' and not an alternative instance of Variable.) These are referred to as 'out' arguments.


The query itself does not declare at compile time whether an argument is in or an out. This can be defined purely at runtime on each use.

Chapter 14. Domain Specific Languages (DSLs)

14.1. Domain Specific Languages

Domain Specific Languages (or DSLs) are a way of creating a rule language that is dedicated to your problem domain. A set of DSL definitions consists of transformations from DSL "sentences" to DRL constructs, which lets you use of all the underlying rule language and engine features. You can write rules in DSL rule (or DSLR) files, which will be translated into DRL files.
DSL and DSLR files are plain text files and you can use any text editor to create and modify them. There are also DSL and DSLR editors you can use, both in the IDE as well as in the web based BRMS, although they may not provide you with the full DSL functionality.

14.2. Using DSLs

DSLs can serve as a layer of separation between rule authoring (and rule authors) and the technical intricacies resulting from the modeling of domain object and the rule engine's native language and methods. A DSL hides implementation details and focuses on the rule logic proper. DSL sentences can also act as "templates" for conditional elements and consequence actions that are used repeatedly in your rules, possibly with minor variations. You may define DSL sentences as being mapped to these repeated phrases, with parameters providing a means for accommodating those variations.

14.3. DSL Example

Table 14.1. DSL Example

Example Description
[when]Something is {colour}=Something(colour=="{colour}")
[when] indicates the scope of the expression (that is, whether it is valid for the LHS or the RHS of a rule).
The part after the bracketed keyword is the expression that you use in the rule.
The part to the right of the equal sign ("=") is the mapping of the expression into the rule language. The form of this string depends on its destination, RHS or LHS. If it is for the LHS, then it ought to be a term according to the regular LHS syntax; if it is for the RHS then it might be a Java statement.

14.4. How the DSL Parser Works

Whenever the DSL parser matches a line from the rule file written in the DSL with an expression in the DSL definition, it performs three steps of string manipulation:
  • The DSL extracts the string values appearing where the expression contains variable names in brackets.
  • The values obtained from these captures are interpolated wherever that name occurs on the right hand side of the mapping.
  • The interpolated string replaces whatever was matched by the entire expression in the line of the DSL rule file.


You can use (for instance) a '?' to indicate that the preceding character is optional. One good reason to use this is to overcome variations in natural language phrases of your DSL. But, given that these expressions are regular expression patterns, this means that all wildcard characters in Java's pattern syntax have to be escaped with a preceding backslash ('\').

14.5. The DSL Compiler

The DSL compiler transforms DSL rule files line by line. If you do not wish for this to occur, ensure that the captures are surrounded by characteristic text (words or single characters). As a result, the matching operation done by the parser plucks out a substring from somewhere within the line. In the example below, quotes are used as distinctive characters. (The characters that surround the capture are not included during interpolation, just the contents between them.)

14.6. DSL Syntax Examples

Table 14.2. DSL Syntax Examples

Name Description Example
Quotes Use quotes for textual data that a rule editor may want to enter. You can also enclose the capture with words to ensure that the text is correctly matched.
[when]something is "{color}"=Something(color=="{color}")
[when]another {state} thing=OtherThing(state=="{state}"
Braces In a DSL mapping, the braces "{" and "}" should only be used to enclose a variable definition or reference, resulting in a capture. If they should occur literally, either in the expression or within the replacement text on the right hand side, they must be escaped with a preceding backslash ("\").
[then]do something= if (foo) \{ doSomething(); \}
Mapping with correct syntax example n/a
# This is a comment to be ignored.
[when]There is a person with name of "{name}"=Person(name=="{name}")
[when]Person is at least {age} years old and lives in "{location}"=
      Person(age >= {age}, location=="{location}")
[then]Log "{message}"=System.out.println("{message}");
[when]And = and
Expanded DSL example n/a
There is a person with name of "Kitty"
   ==> Person(name="Kitty")
Person is at least 42 years old and lives in "Atlanta"
   ==> Person(age >= 42, location="Atlanta")
Log "boo"
   ==> System.out.println("boo");
There is a person with name of "Bob" and Person is at least 30 years old and lives in "Utah"
   ==> Person(name="Bob") and Person(age >= 30, location="Utah")


If you are capturing plain text from a DSL rule line and want to use it as a string literal in the expansion, you must provide the quotes on the right hand side of the mapping.

14.7. Chaining DSL Expressions

DSL expressions can be chained together one one line to be used at once. It must be clear where one ends and the next one begins and where the text representing a parameter ends. (Otherwise you risk getting all the text until the end of the line as a parameter value.) The DSL expressions are tried, one after the other, according to their order in the DSL definition file. After any match, all remaining DSL expressions are investigated, too.

14.8. Adding Constraints to Facts

Table 14.3. Adding Constraints to Facts

Name Description Example
Expressing LHS conditions
The DSL facility allows you to add constraints to a pattern by a simple convention: if your DSL expression starts with a hyphen (minus character, "-") it is assumed to be a field constraint and, consequently, is is added to the last pattern line preceding it.
In the example, the class Cheese, has these fields: type, price, age and country. You can express some LHS condition in normal DRL.
Cheese(age < 5, price == 20, type=="stilton", country=="ch")
DSL definitions
The DSL definitions given in this example result in three DSL phrases which may be used to create any combination of constraint involving these fields.
[when]There is a Cheese with=Cheese()
[when]- age is less than {age}=age<{age}
[when]- type is '{type}'=type=='{type}'
[when]- country equal to '{country}'=country=='{country}'
The parser will pick up a line beginning with "-" and add it as a constraint to the preceding pattern, inserting a comma when it is required.
There is a Cheese with
        - age is less than 42
        - type is 'stilton'
Cheese(age<42, type=='stilton')
Defining DSL phrases
Defining DSL phrases for various operators and even a generic expression that handles any field constraint reduces the amount of DSL entries.
[when][]is less than or equal to=<=
[when][]is less than=<
[when][]is greater than or equal to=>=
[when][]is greater than=>
[when][]is equal to===
[when][]There is a Cheese with=Cheese()
[when][]- {field:\w*} {operator} {value:\d*}={field} {operator} {value}
DSL definition rule n/a
There is a Cheese with
   - age is less than 42
   - rating is greater than 50
   - type equals 'stilton'
In this specific case, a phrase such as "is less than" is replaced by <, and then the line matches the last DSL entry. This removes the hyphen, but the final result is still added as a constraint to the preceding pattern. After processing all of the lines, the resulting DRL text is:
Cheese(age<42, rating > 50, type=='stilton')


The order of the entries in the DSL is important if separate DSL expressions are intended to match the same line, one after the other.

14.9. Tips for Developing DSLs

  • Write representative samples of the rules your application requires and test them as you develop.
  • Rules, both in DRL and in DSLR, refer to entities according to the data model representing the application data that should be subject to the reasoning process defined in rules.
  • Writing rules is easier if most of the data model's types are facts.
  • Mark variable parts as parameters. This provides reliable leads for useful DSL entries.
  • You may postpone implementation decisions concerning conditions and actions during this first design phase by leaving certain conditional elements and actions in their DRL form by prefixing a line with a greater sign (">"). (This is also handy for inserting debugging statements.)
  • New rules can be written by reusing the existing DSL definitions, or by adding a parameter to an existing condition or consequence entry.
  • Keep the number of DSL entries small. Using parameters lets you apply the same DSL sentence for similar rule patterns or constraints.

14.10. DSL and DSLR Reference

A DSL file is a text file in a line-oriented format. Its entries are used for transforming a DSLR file into a file according to DRL syntax:
  • A line starting with "#" or "//" (with or without preceding white space) is treated as a comment. A comment line starting with "#/" is scanned for words requesting a debug option, see below.
  • Any line starting with an opening bracket ("[") is assumed to be the first line of a DSL entry definition.
  • Any other line is appended to the preceding DSL entry definition, with the line end replaced by a space.

14.11. The Make Up of a DSL Entry

A DSL entry consists of the following four parts:
  • A scope definition, written as one of the keywords "when" or "condition", "then" or "consequence", "*" and "keyword", enclosed in brackets ("[" and "]"). This indicates whether the DSL entry is valid for the condition or the consequence of a rule, or both. A scope indication of "keyword" means that the entry has global significance, that is, it is recognized anywhere in a DSLR file.
  • A type definition, written as a Java class name, enclosed in brackets. This part is optional unless the next part begins with an opening bracket. An empty pair of brackets is valid, too.
  • A DSL expression consists of a (Java) regular expression, with any number of embedded variable definitions, terminated by an equal sign ("="). A variable definition is enclosed in braces ("{" and "}"). It consists of a variable name and two optional attachments, separated by colons (":"). If there is one attachment, it is a regular expression for matching text that is to be assigned to the variable. If there are two attachments, the first one is a hint for the GUI editor and the second one the regular expression.
    Note that all characters that are "magic" in regular expressions must be escaped with a preceding backslash ("\") if they should occur literally within the expression.
  • The remaining part of the line after the delimiting equal sign is the replacement text for any DSLR text matching the regular expression. It may contain variable references, i.e., a variable name enclosed in braces. Optionally, the variable name may be followed by an exclamation mark ("!") and a transformation function, see below.
    Note that braces ("{" and "}") must be escaped with a preceding backslash ("\") if they should occur literally within the replacement string.

14.12. Debug Options for DSL Expansion

Table 14.4. Debug Options for DSL Expansion

Word Description
result Prints the resulting DRL text, with line numbers.
steps Prints each expansion step of condition and consequence lines.
keyword Dumps the internal representation of all DSL entries with scope "keyword".
when Dumps the internal representation of all DSL entries with scope "when" or "*".
then Dumps the internal representation of all DSL entries with scope "then" or "*".
usage Displays a usage statistic of all DSL entries.

14.13. DSL Definition Example

This is what a DSL definition looks like:
# Comment: DSL examples

#/ debug: display result and usage

# keyword definition: replaces "regula" by "rule"

# conditional element: "T" or "t", "a" or "an", convert matched word
[when][][Tt]here is an? {entity:\w+}=
        ${entity!lc}: {entity!ucfirst} ()

# consequence statement: convert matched word, literal braces
[then][]update {entity:\w+}=modify( ${entity!lc} )\{ \}

14.14. Transformation of a DSLR File

The transformation of a DSLR file proceeds as follows:
  1. The text is read into memory.
  2. Each of the "keyword" entries is applied to the entire text. The regular expression from the keyword definition is modified by replacing white space sequences with a pattern matching any number of white space characters, and by replacing variable definitions with a capture made from the regular expression provided with the definition, or with the default (".*?"). Then, the DSLR text is searched exhaustively for occurrences of strings matching the modified regular expression. Substrings of a matching string corresponding to variable captures are extracted and replace variable references in the corresponding replacement text, and this text replaces the matching string in the DSLR text.
  3. Sections of the DSLR text between "when" and "then", and "then" and "end", respectively, are located and processed in a uniform manner, line by line, as described below.
    For a line, each DSL entry pertaining to the line's section is taken in turn, in the order it appears in the DSL file. Its regular expression part is modified: white space is replaced by a pattern matching any number of white space characters; variable definitions with a regular expression are replaced by a capture with this regular expression, its default being ".*?". If the resulting regular expression matches all or part of the line, the matched part is replaced by the suitably modified replacement text.
    Modification of the replacement text is done by replacing variable references with the text corresponding to the regular expression capture. This text may be modified according to the string transformation function given in the variable reference; see below for details.
    If there is a variable reference naming a variable that is not defined in the same entry, the expander substitutes a value bound to a variable of that name, provided it was defined in one of the preceding lines of the current rule.
  4. If a DSLR line in a condition is written with a leading hyphen, the expanded result is inserted into the last line, which should contain a pattern CE, that is, a type name followed by a pair of parentheses. if this pair is empty, the expanded line (which should contain a valid constraint) is simply inserted, otherwise a comma (",") is inserted beforehand.
    If a DSLR line in a consequence is written with a leading hyphen, the expanded result is inserted into the last line, which should contain a "modify" statement, ending in a pair of braces ("{" and "}"). If this pair is empty, the expanded line (which should contain a valid method call) is simply inserted, otherwise a comma (",") is inserted beforehand.


It is currently not possible to use a line with a leading hyphen to insert text into other conditional element forms (e.g., "accumulate") or it may only work for the first insertion (e.g., "eval").

14.15. String Transformation Functions

Table 14.5. String Transformation Functions

Name Description
uc Converts all letters to upper case.
lc Converts all letters to lower case.
ucfirst Converts the first letter to upper case, and all other letters to lower case.
num Extracts all digits and "-" from the string. If the last two digits in the original string are preceded by "." or ",", a decimal period is inserted in the corresponding position.
a?b/c Compares the string with string a, and if they are equal, replaces it with b, otherwise with c. But c can be another triplet a, b, c, so that the entire structure is, in fact, a translation table.

14.16. Stringing DSL Transformation Functions

Table 14.6. Stringing DSL Transformation Functions

Name Description Example
A file containing a DSL definition is customarily given the extension .dsl. It is passed to the Knowledge Builder with ResourceType.DSL. For a file using DSL definition, the extension .dslr should be used. The Knowledge Builder expects ResourceType.DSLR. The IDE, however, relies on file extensions to correctly recognize and work with your rules file.
# definitions for conditions
[when][]There is an? {entity}=${entity!lc}: {entity!ucfirst}()
[when][]- with an? {attr} greater than {amount}={attr} <= {amount!num}
[when][]- with a {what} {attr}={attr} {what!positive?>0/negative?%lt;0/zero?==0/ERROR}
DSL passing
The DSL must be passed to the Knowledge Builder ahead of any rules file using the DSL.
For parsing and expanding a DSLR file the DSL configuration is read and supplied to the parser. Thus, the parser can "recognize" the DSL expressions and transform them into native rule language expressions.
KnowledgeBuilder kBuilder = new KnowledgeBuilder();
Resource dsl = ResourceFactory.newClassPathResource( dslPath, getClass() );
kBuilder.add( dsl, ResourceType.DSL );
Resource dslr = ResourceFactory.newClassPathResource( dslrPath, getClass() );
kBuilder.add( dslr, ResourceType.DSLR );

Chapter 15. XML

15.1. The XML Format


The XML rule language has not been updated to support functionality introduced in Drools 5.x and is consider a deprecated feature.
As an option, JBoss Rules supports a "native" rule language as an alternative to DRL. This allows you to capture and manage your rules as XML data. Just like the non-XML DRL format, the XML format is parsed into the internal "AST" representation as fast as possible (using a SAX parser). There is no external transformation step required.

15.2. XML Rule Example

This is what a rule looks like in XML:
<?xml version="1.0" encoding="UTF-8"?>

<package name="com.sample"
         xs:schemaLocation="http://drools.org/drools-5.0 drools-5.0.xsd">

<import name="java.util.HashMap" />
<import name="org.drools.*" />

<global identifier="x" type="com.sample.X" />
<global identifier="yada" type="com.sample.Yada" />

<function return-type="void" name="myFunc">
    <parameter identifier="foo" type="Bar" />
    <parameter identifier="bada" type="Bing" />

     System.out.println("hello world");

<rule name="simple_rule">
<rule-attribute name="salience" value="10" />
<rule-attribute name="no-loop" value="true" />
<rule-attribute name="agenda-group" value="agenda-group" />
<rule-attribute name="activation-group" value="activation-group" />

    <pattern identifier="foo2" object-type="Bar" >
                    <field-constraint field-name="a">
                                <literal-restriction evaluator=">" value="60" />
                                <literal-restriction evaluator="<" value="70" />
                                <literal-restriction evaluator="<" value="50" />
                                <literal-restriction evaluator=">" value="55" />

                    <field-constraint field-name="a3">
                        <literal-restriction evaluator="==" value="black" />

                    <field-constraint field-name="a">
                        <literal-restriction evaluator="==" value="40" />

                    <field-constraint field-name="a3">
                        <literal-restriction evaluator="==" value="pink" />

                    <field-constraint field-name="a">
                        <literal-restriction evaluator="==" value="12"/>

                    <field-constraint field-name="a3">
                            <literal-restriction evaluator="==" value="yellow"/>
                            <literal-restriction evaluator="==" value="blue" />

            <pattern object-type="Person">
                <field-constraint field-name="likes">
                    <variable-restriction evaluator="==" identifier="type"/>

                <pattern object-type="Person">
                    <field-constraint field-name="likes">
                        <variable-restriction evaluator="==" identifier="type"/>

            <pattern identifier="foo3" object-type="Bar" >
                <field-constraint field-name="a">
                        <literal-restriction evaluator="==" value="3" />
                        <literal-restriction evaluator="==" value="4" />
                <field-constraint field-name="a3">
                    <literal-restriction evaluator="==" value="hello" />
                <field-constraint field-name="a4">
                    <literal-restriction evaluator="==" value="null" />

            <pattern identifier="foo4" object-type="Bar" >
                <field-binding field-name="a" identifier="a4" />
                <field-constraint field-name="a">
                    <literal-restriction evaluator="!=" value="4" />
                    <literal-restriction evaluator="!=" value="5" />

        <pattern identifier="foo5" object-type="Bar" >
            <field-constraint field-name="b">
                    <return-value-restriction evaluator="==" >a4 + 1</return-value-restriction>
                    <variable-restriction evaluator=">" identifier="a4" />
                    <qualified-identifier-restriction evaluator="==">

        <pattern identifier="foo6" object-type="Bar" >
            <field-binding field-name="a" identifier="a4" />
            <field-constraint field-name="b">
                <literal-restriction evaluator="==" value="6" />
    if ( a == b ) {
      assert( foo3 );
    } else {
      retract( foo4 );
    System.out.println( a4 );


15.3. XML Elements

Table 15.1. XML Elements

Name Description
Defines global objects that can be referred to in the rules.
Contains a function declaration for a function to be used in the rules. You have to specify a return type, a unique name and parameters, in the body goes a snippet of code.
Imports the types you wish to use in the rule.

15.4. Detail of a Rule Element

This example rule has LHS and RHS (conditions and consequence) sections. The RHS is a block of semantic code that will be executed when the rule is activated. The LHS is slightly more complicated as it contains nested elements for conditional elements, constraints and restrictions:
<rule name="simple_rule">
<rule-attribute name="salience" value="10" />
<rule-attribute name="no-loop" value="true" />
<rule-attribute name="agenda-group" value="agenda-group" />
<rule-attribute name="activation-group" value="activation-group" />

    <pattern identifier="cheese" object-type="Cheese">
                <pattern object-type="Person"></pattern>
                    int total = 0;
                    total += $cheese.getPrice();
                    new Integer( total ) );

    <pattern identifier="max" object-type="Number">
                <pattern identifier="cheese" object-type="Cheese"></pattern>
                <external-function evaluator="max" expression="$price"/>
    list1.add( $cheese );

15.5. XML Rule Elements

Table 15.2. XML Rule Elements

Element Description
This allows you to specify a type (class) and perhaps bind a variable to an instance of that class. Nested under the pattern object are constraints and restrictions that have to be met. The Predicate and Return Value constraints allow Java expressions to be embedded.
Conditional elements (not, exists, and, or)
These work like their DRL counterparts. Elements that are nested under and an "and" element are logically "anded" together. Likewise with "or" (and you can nest things further). "Exists" and "Not" work around patterns, to check for the existence or nonexistence of a fact meeting the pattern's constraints.
Allows the execution of a valid snippet of Java code as long as it evaluates to a boolean (do not end it with a semi-colon, as it is just a fragment). This can include calling a function. The Eval is less efficient than the columns, as the rule engine has to evaluate it each time, but it is a "catch all" feature for when you can express what you need to do with Column constraints.

15.6. Automatic Transforming Between XML and DRL

JBoss Rules comes with some utility classes to transform between formats. This works by parsing the rules from the source format into the AST and then "dumping" out to the appropriate target format. This allows you to, for example, write rules in DRL and export them to XML.

15.7. Classes for Automatic Transforming Between XML and DRL

These are the classes to use when transforming between XML and DRL files. Using combinations of these, you can convert between any format (including round trip):
  • DrlDumper - for exporting DRL
  • DrlParser - for reading DRL
  • XmlPackageReader - for reading XML


DSLs will not be preserved (from DRLs that are using a DSL) - but they will be able to be converted.

Chapter 16. Decision Tables

16.1. Decision Tables

Decision tables are a way of representing conditional logic. They are well suited to business level rules.

16.2. Decision Tables in Spreadsheets

JBoss Rules supports managing rules in a spreadsheet format. Supported formats are Excel (XLS) and CSV. This means that a variety of spreadsheet programs (such as Microsoft Excel, OpenOffice.org Calc, and others) can be utilized.

16.3. Open Office Example

Open Office Screenshot

Figure 16.1. Open Office Screenshot

In the above examples, the technical aspects of the decision table have been collapsed away (using a standard spreadsheet feature).
The rules start from row 17, with each row resulting in a rule. The conditions are in columns C, D, E, etc., and the actions are off-screen. The values' meanings are indicated by the headers in Row 16. (Column B is just a description.)


Although the decision tables look like they process top down, this is not necessarily the case. Ideally, rules are authored without regard for the order of rows. This makes maintenance easier, as rows will not need to be shifted around all the time.

16.4. Rules and Spreadsheets

Rules inserted into rows
As each row is a rule, the same principles apply as with written code. As the rule engine processes the facts, any rules that match may fire.
It is possible to clear the agenda when a rule fires and simulate a very simple decision table where only the first match effects an action.
Multiple tables
You can have multiple tables on one spreadsheet. This way, rules can be grouped where they share common templates, but are still all combined into one rule package.

16.5. The RuleTable Keyword

When using decision tables, the spreadsheet searches for the RuleTable keyword to indicate the start of a rule table (both the starting row and column).


Keywords should all be in the same column.

16.6. The RuleSet Keyword

The RuleSet keyword indicates the name to be used in the rule package that will encompass all the rules. This name is optional, using a default, but it must have the RuleSet keyword in the cell immediately to the right.

16.7. Rule Template Example

Rule Template

Figure 16.2. Rule Template

  • The RuleSet keyword indicates the name to be used in the rule package that will encompass all the rules. This name is optional, using a default, but it must have the RuleSet keyword in the cell immediately to the right. The other keywords visible in Column C are Import and Sequential.
  • After the RuleTable keyword there is a name, used to prefix the names of the generated rules. The row numbers are appended to guarantee unique rule names.
  • The column of RuleTable indicates the column in which the rules start; columns to the left are ignored.
  • Referring to row 14 (the row immediately after RuleTable), the keywords CONDITION and ACTION indicate that the data in the columns below are for either the LHS or the RHS parts of a rule. There are other attributes on the rule which can also be optionally set this way.
  • Row 15 contains declarations of ObjectTypes. The content in this row is optional, but if this option is not in use, the row must be left blank. When using this row, the values in the cells below (row 16) become constraints on that object type. In the above case, it generates Person(age=="42") and Cheese(type=="stilton"), where 42 and "stilton" come from row 18. In the above example, the "==" is implicit. If just a field name is given, the translator assumes that it is to generate an exact match.
  • Row 16 contains the rule templates themselves. They can use the "$param" placeholder to indicate where data from the cells below should be interpolated. (For multiple insertions, use "$1", "$2", etc., indicating parameters from a comma-separated list in a cell below.) Row 17 is ignored. It may contain textual descriptions of the column's purpose.
  • Rows 18 and 19 show data, which will be combined (interpolated) with the templates in row 15, to generate rules. If a cell contains no data, then its template is ignored. (This would mean that some condition or action does not apply for that rule row.) Rule rows are read until there is a blank row. Multiple RuleTables can exist in a sheet.
  • Row 20 contains another keyword, and a value. The row positions of keywords like this do not matter (most people put them at the top) but their column should be the same one where the RuleTable or RuleSet keywords should appear. In our case column C has been chosen to be significant, but any other column could be used instead.


An ObjectType declaration can span columns (via merged cells), meaning that all columns below the merged range are to be combined into one set of constraints within a single pattern matching a single fact at a time, as opposed to non-merged cells containing the same ObjectType, but resulting in different patterns, potentially matching different or identical facts.
In the above example, rules would be rendered like the following (as it uses the "ObjectType" row):
//row 18
rule "Cheese_fans_18"
    list.add("Old man stilton");


The constraints age=="42" and type=="stilton" are interpreted as single constraints, to be added to the respective ObjectType in the cell above. If the cells above were spanned, then there could be multiple constraints on one "column".


Very large decision tables may have very large memory requirements.

16.8. Data-Defining Cells

There are two types of rectangular areas defining data that is used for generating a DRL file. One, marked by a cell labelled RuleSet, defines all DRL items except rules. The other one may occur repeatedly and is to the right and below a cell whose contents begin with RuleTable. These areas represent the actual decision tables, each area resulting in a set of rules of similar structure.
A Rule Set area may contain cell pairs, one below the RuleSet cell and containing a keyword designating the kind of value contained in the other one that follows in the same row.

16.9. Rule Table Columns

The columns of a Rule Table area define patterns and constraints for the left hand sides of the rules derived from it, actions for the consequences of the rules, and the values of individual rule attributes. A Rule Table area should contain one or more columns, both for conditions and actions, and an arbitrary selection of columns for rule attributes, at most one column for each of these. The first four rows following the row with the cell marked with RuleTable are earmarked as header area, mostly used for the definition of code to construct the rules. It is any additional row below these four header rows that spawns another rule, with its data providing for variations in the code defined in the Rule Table header.


All keywords are case insensitive.
Only the first worksheet is examined for decision tables.

16.10. Rule Set Entries

Entries in a Rule Set area may define DRL constructs (except rules), and specify rule attributes. While entries for constructs may be used repeatedly, each rule attribute may be given at most once, and it applies to all rules unless it is overruled by the same attribute being defined within the Rule Table area.
Entries must be given in a vertically stacked sequence of cell pairs. The first one contains a keyword and the one to its right the value. This sequence of cell pairs may be interrupted by blank rows or even a Rule Table, as long as the column marked by RuleSet is upheld as the one containing the keyword.

16.11. Entries in the Rule Set Area

Table 16.1. Entries in the Rule Set area

Keyword Value Usage
RuleSet The package name for the generated DRL file. Optional, the default is rule_table. Must be First entry.
Sequential "true" or "false". If "true", then salience is used to ensure that rules fire from the top down. Optional, at most once. If omitted, no firing order is imposed.
EscapeQuotes "true" or "false". If "true", then quotation marks are escaped so that they appear literally in the DRL. Optional, at most once. If omitted, quotation marks are escaped.
Import A comma-separated list of Java classes to import. Optional, may be used repeatedly.
Variables Declarations of DRL globals, i.e., a type followed by a variable name. Multiple global definitions must be separated with a comma. Optional, may be used repeatedly.
Functions One or more function definitions, according to DRL syntax. Optional, may be used repeatedly.
Queries One or more query definitions, according to DRL syntax. Optional, may be used repeatedly.
Declare One or more declarative types, according to DRL syntax. Optional, may be used repeatedly.

16.12. Rule Attribute Entries in the Rule Set Area

Table 16.2. Rule Attribute Entries in the Rule Set Area

Keyword Initial Value
PRIORITY P An integer defining the "salience" value for the rule. Overridden by the "Sequential" flag.
DURATION D A long integer value defining the "duration" value for the rule.
TIMER T A timer definition. See "Timers and Calendars".
CALENDARS E A calendars definition. See "Timers and Calendars".
NO-LOOP U A Boolean value. "true" inhibits looping of rules due to changes made by its consequence.
LOCK-ON-ACTIVE L A Boolean value. "true" inhibits additional activations of all rules with this flag set within the same ruleflow or agenda group.
AUTO-FOCUS F A Boolean value. "true" for a rule within an agenda group causes activations of the rule to automatically give the focus to the group.
ACTIVATION-GROUP X A string identifying an activation (or XOR) group. Only one rule within an activation group will fire, i.e., the first one to fire cancels any existing activations of other rules within the same group.
AGENDA-GROUP G A string identifying an agenda group, which has to be activated by giving it the "focus", which is one way of controlling the flow between groups of rules.
RULEFLOW-GROUP R A string identifying a rule-flow group.

16.13. The RuleTable Cell

All Rule Tables begin with a cell containing "RuleTable", optionally followed by a string within the same cell. The string is used as the initial part of the name for all rules derived from this Rule Table, with the row number appended for distinction. (This automatic naming can be overridden by using a NAME column.) All other cells defining rules of this Rule Table are below and to the right of this cell.

16.14. Column Types

The next row after the RuleTable cell defines the column type. Each column results in a part of the condition or the consequence, or provides some rule attribute, the rule name or a comment. Each attribute column may be used at most once.

16.15. Column Headers in the Rule Table

Table 16.3. Column Headers in the Rule Table

Keyword Initial Value Usage
NAME N Provides the name for the rule generated from that row. The default is constructed from the text following the RuleTable tag and the row number. At most one column
DESCRIPTION I A text, resulting in a comment within the generated rule. At most one column
CONDITION C Code snippet and interpolated values for constructing a constraint within a pattern in a condition. At least one per rule table
ACTION A Code snippet and interpolated values for constructing an action for the consequence of the rule. At least one per rule table
METADATA @ Code snippet and interpolated values for constructing a metadata entry for the rule. Optional, any number of columns

16.16. Conditional Elements

Given a column headed CONDITION, the cells in successive lines result in a conditional element.
  • Text in the first cell below CONDITION develops into a pattern for the rule condition, with the snippet in the next line becoming a constraint. If the cell is merged with one or more neighbours, a single pattern with multiple constraints is formed: all constraints are combined into a parenthesized list and appended to the text in this cell. The cell may be left blank, which means that the code snippet in the next row must result in a valid conditional element on its own.
    To include a pattern without constraints, you can write the pattern in front of the text for another pattern.
    The pattern may be written with or without an empty pair of parentheses. A "from" clause may be appended to the pattern.
    If the pattern ends with "eval", code snippets are supposed to produce boolean expressions for inclusion into a pair of parentheses after "eval".
  • Text in the second cell below CONDITION is processed in two steps.
    1. The code snippet in this cell is modified by interpolating values from cells farther down in the column. If you want to create a constraint consisting of a comparison using "==" with the value from the cells below, the field selector alone is sufficient. Any other comparison operator must be specified as the last item within the snippet, and the value from the cells below is appended. For all other constraint forms, you must mark the position for including the contents of a cell with the symbol $param. Multiple insertions are possible by using the symbols $1, $2, etc., and a comma-separated list of values in the cells below.
      A text according to the pattern forall(delimiter){snippet} is expanded by repeating the snippet once for each of the values of the comma-separated list of values in each of the cells below, inserting the value in place of the symbol $ and by joining these expansions by the given delimiter. Note that the forall construct may be surrounded by other text.
    2. If the cell in the preceding row is not empty, the completed code snippet is added to the conditional element from that cell. A pair of parentheses is provided automatically, as well as a separating comma if multiple constraints are added to a pattern in a merged cell.
      If the cell above is empty, the interpolated result is used as is.
  • Text in the third cell below CONDITION is for documentation only. It should be used to indicate the column's purpose to a human reader.
  • From the fourth row on, non-blank entries provide data for interpolation as described above. A blank cell results in the omission of the conditional element or constraint for this rule.

16.17. Action Statements

Given a column headed ACTION, the cells in successive lines result in an action statement:
  • Text in the first cell below ACTION is optional. If present, it is interpreted as an object reference.
  • Text in the second cell below ACTION is processed in two steps.
    1. The code snippet in this cell is modified by interpolating values from cells farther down in the column. For a singular insertion, mark the position for including the contents of a cell with the symbol $param. Multiple insertions are possible by using the symbols $1, $2, etc., and a comma-separated list of values in the cells below.
      A method call without interpolation can be achieved by a text without any marker symbols. In this case, use any non-blank entry in a row below to include the statement.
      The forall construct is available here, too.
    2. If the first cell is not empty, its text, followed by a period, the text in the second cell and a terminating semicolon are stringed together, resulting in a method call which is added as an action statement for the consequence.
      If the cell above is empty, the interpolated result is used as is.
  • Text in the third cell below ACTION is for documentation only. It should be used to indicate the column's purpose to a human reader.
  • From the fourth row on, non-blank entries provide data for interpolation as described above. A blank cell results in the omission of the action statement for this rule.


Using $1 instead of $param will fail if the replacement text contains a comma.

16.18. Metadata Statements

Given a column headed METADATA, the cells in successive lines result in a metadata annotation for the generated rules:
  • Text in the first cell below METADATA is ignored.
  • Text in the second cell below METADATA is subject to interpolation, as described above, using values from the cells in the rule rows. The metadata marker character @ is prefixed automatically, and should not be included in the text for this cell.
  • Text in the third cell below METADATA is for documentation only. It should be used to indicate the column's purpose to a human reader.
  • From the fourth row on, non-blank entries provide data for interpolation as described above. A blank cell results in the omission of the metadata annotation for this rule.

16.19. Interpolating Cell Data Example

  • If the template is Foo(bar == $param) and the cell is 42, then the result is Foo(bar == 42).
  • If the template is Foo(bar < $1, baz == $2) and the cell contains 42,43, the result will be Foo(bar < 42, baz ==43).
  • The template forall(&&){bar != $} with a cell containing 42,43 results in bar != 42 && bar != 43.

16.20. Tips for Working Within Cells

  • Multiple package names within the same cell must be comma-separated.
  • Pairs of type and variable names must be comma-separated.
  • Functions must be written as they appear in a DRL file. This should appear in the same column as the "RuleSet" keyword. It can be above, between or below all the rule rows.
  • You can use Import, Variables, Functions and Queries repeatedly instead of packing several definitions into a single cell.
  • Trailing insertion markers can be omitted.
  • You can provide the definition of a binding variable.
  • Anything can be placed in the object type row. Apart from the definition of a binding variable, it could also be an additional pattern that is to be inserted literally.
  • The cell below the ACTION header can be left blank. Using this style, anything can be placed in the consequence, not just a single method call. (The same technique is applicable within a CONDITION column.)

16.21. The SpreadsheetCompiler Class

The SpreadsheetCompiler class is the main class used with API spreadsheet-based decision tables in the drools-decisiontables module. This class takes spreadsheets in various formats and generates rules in DRL.
The SpreadsheetCompiler can be used to generate partial rule files and assemble them into a complete rule package after the fact. This allows the separation of technical and non-technical aspects of the rules if needed.

16.22. Using Spreadsheet-Based Decision Tables

Procedure 16.1. Task

  1. Generate a sample spreadsheet can to use as the base.
  2. If the Rule Workbench IDE plug-in is being used, use the wizard to generate a spreadsheet from a template.
  3. Use an XSL-compatible spreadsheet editor to modify the XSL.

16.23. Lists

In Excel, you can create lists of values. These can be stored in other worksheets to provide valid lists of values for cells.

16.24. Revision Control

When changes are being made to rules over time, older versions are archived. Some applications in JBoss Rules provide a limited ability to keep a history of changes, but it is recommended to use an alternative means of revision control.

16.25. Tabular Data Sources

A tabular data source can be used as a source of rule data. It can populate a template to generate many rules. This can allow both for more flexible spreadsheets, but also rules in existing databases for instance (at the cost of developing the template up front to generate the rules).

Chapter 17. The Java Rule Engine Application Programming Interface

17.1. JSR94

JSR94 is an API used in JBoss Rules. It allows for support of multiple rule engines from a single API. JSR94 does not deal in any way with the rule language itself.
The JSR94 standard represents the "least common denominator" in features across rule engines. This means that there is less functionality in the JSR94 API than in the standard Knowledge API. By using JSR94, you cannot use all the capabilities of JBoss Rules. You should use globals and support for DRL, DSL and XML, via property maps in conjunction with JSR94. This introduces non-portable functionality.


As JSR94 does not provide a rule language, you are only solving a small fraction of the complexity of switching rule engines with very little gain. Red Hat recommends you program against the Knowledge (JBoss Rules and jBPM) API.

17.2. Javax.rules Interfaces

  • Handle
    The Handle is used to retrieve an Object back from the WorkingMemory which was added in a StatefulRuleSession . With the Handle you can modify or remove an Object from the WorkingMemory. To modify an Object call updateObject() from the StatefulRuleSession. To remove it, call removeObject() with the Handle as the Parameter. Inside of the implementation of the Java Rule Engine API will be called the modifyObject() and retractObject() methods of the encapsulated Knowledge (Drools and jBPM) API.
  • ObjectFilter
    This interface is used to filter objects for RuleSession.
  • RuleExecutionSetMetadata
    The RuleExecutionSetMetadata is used to store name, description and URI for a RuleExecutionSet.
  • RuleRuntime
    The RuleRuntime is the key to a RuleSession. The RuleRuntime obtained from the RuleServiceProvider.
    If you retrieve a RuleRuntime call createRuleSession() to open a RuleSession.
    Through the RuleRuntime you can retrieve a list of URIs of all RuleExecutionSets, which were registered by a RuleAdministrator. You need the URI as a String to open a RuleSession to the rule engine. The rule engine will use the rules of the RuleExecutionSet inside of the RuleSession.
    The Map is used for Globals. Globals were formerly called ApplicationData (in Drools 2.x). The key needs to be the identifier of the Global and the Value the object you want to use as a Global.
  • RuleSession
    The RuleSession is the object you are working with if you want to contact the rule engine.
    If you are getting a RuleSession from the RuleRuntime, then it will be either a StatefulRuleSession or a StatelessRuleSession.
    Call the release()-method so that all resources will be freed.
  • StatefulRuleSession
    If you need to run the rule engine more than once, run a StatefulRuleSession. You can assert objects, execute rules and so on.
    You will get a Handle for every object which you are asserting to the Rule Session. Do not lose it, you will need it, to retract or modify objects in the Working Memory. You are having no direct contact to Drools´ Working Memory which is used inside the implementation, for this you got the RuleSession.
  • StatelessRuleSession
    A StatelessRuleSession means that you are having only one contact to the rule engine. You are giving a list of objects to the rule engine and the rule engine asserts them all and starts execution immediately. The result is a list of objects. The content of the result list depends on your rules. If your rules are not modifying or retracting any objects from the Working Memory, you should get all objects you re-added.
    You can use the ObjectFilter which will filter the resulting list of objects before you get it.

17.3. Javax.rules Classes

  • RuleServiceProvider
    The RuleServiceProvider gives you access to the RuleAdministrator or a RuleRuntime, which you need to open a new Rule Session. To get the RuleServiceProvider call RuleServiceProviderManager.getRuleServiceProvider().
    In a J2EE environment you can bind the RuleServiceProvider to the JNDI and create a lookup to place it in all your applications.
  • RuleServiceProviderManager
    The RuleServiceProvider is often compared with the DriverManager, which you use in JDBC. It works like setting up the Driver for a DataBase.

17.4. Javax.rules Exceptions

  • ConfigurationException
    This exception is thrown when a user configuration error has been made.
  • InvalidHandleException
    This exception is thrown when a client passes an invalid Handle to the rule engine.
  • InvalidRuleSessionException
    The InvalidRuleSessionException should be thrown when a method is invoked on a RuleSession and the internal state of the RuleSession is invalid. This may have occurred because a StatefulRuleSession has been serialized and external resources can no longer be accessed. This exception is also used to signal that a RuleSession is in an invalid state (such as an attempt to use it after the release method has been called) (Taken from JCP API Documentation).
  • RuleException
    Base class for all Exception classes in the javax.rules package.
  • RuleExecutionException
    This exception is not thrown in the Drools 3 JSR 94 implementation
  • RuleExecutionSetNotFoundException
    This exception is thrown if a client requests a RuleExecutionSet from the RuleRuntime and the URI or RuleExecutionSet cannot be found (Taken from JCP API Documentation).
  • RuleSessionCreateException
    This exception is thrown when a client requests a RuleSession from the RuleRuntime and an error occurs that prevents a RuleSession from being returned (Taken from JCP API Documentation).
  • RuleSessionTypeUnsupportedException
    This exception is thrown when a client requests a RuleSession and the vendor does not support the given type (defined in the RuleRuntime) or the RuleExecutionSet itself does not support the requested mode (Taken from JCP API Documentation).

17.5. Using a Rule Service Provider

Procedure 17.1. Task

  1. Use the following code to load the JBoss Rules rule service provider:
    Class ruleServiceProviderClass = Class.forName("org.drools.jsr94.rules.RuleServiceProviderImpl");
  2. Use the following code to register it:
    RuleServiceProviderManager.registerRuleServiceProvider( "http://jboss.com/products/rules", ruleServiceProviderClass);
  3. Call to the RuleServiceProvider using the following code:
  4. To stop the rule service, deregister it with this code:
    RuleServiceProviderManager.deregisterRuleServiceProvider( "http://jboss.com/products/rules");

17.6. Javax.rules.admin Interfaces

  • LocalRuleExecutionSetProvider
  • Rule
  • RuleAdministrator
  • RuleExecutionSet
  • RuleExecutionSetProvider

17.7. Javax.rules.admin Exceptions

  • RuleAdministrationException
    Base class for all administration RuleException classes in the javax.rules.admin package (Taken from JCP API Documentation).
  • RuleExecutionSetCreateException
    Occurs when there is an error in creating a rule execution set.
  • RuleExecutionSetDeregistrationException
    Occurs if there is an error upon attempting to unregister a rule execution set from a URI.
  • RuleExecutionSetRegisterException
    Occurs if there is an error upon attempting to register a rule execution set to a URI.

17.8. The RuleServiceProvider

The RuleServiceProvider provides access to the RuleRuntime and RuleAdministrator APIs. The RuleAdministrator provides an administration API for the management of RuleExecutionSet objects, making it possible to register a RuleExecutionSet that can then be retrieved via the RuleRuntime.

17.9. The RuleServiceProviderManager

The RuleServiceProviderManager manages the registration and retrieval of RuleServiceProviders. The JBossRules RuleServiceProvider implementation is automatically registered via a static block when the class is loaded using Class.forName, in much the same way as JDBC drivers.

17.10. Automatic RuleServiceProvider Registration Example

This is an example of registering the automatic RuleServiceProvider:
// RuleServiceProviderImpl is registered to "http://drools.org/"
// via a static initialization block

// Get the rule service provider from the provider manager.
RuleServiceProvider ruleServiceProvider =

17.11. Registering a LocalRuleExecutionSet with the RuleAdministrator API

Procedure 17.2. Task

  1. Create a RuleExecutionSet. You can do so by using the RuleAdministrator which provides factory methods to return an empty LocalRuleExecutionSetProvider or RuleExecutionSetProvider.
  2. Specify the name for the RuleExecutionSet.
  3. Register the RuleExecutionSet as shown below:
    // Register the RuleExecutionSet with the RuleAdministrator
    String uri = ruleExecutionSet.getName();
    ruleAdministrator.registerRuleExecutionSet(uri, ruleExecutionSet, null);
  4. Use the LocalRuleExecutionSetProvider to load a RuleExecutionSets from local sources that are not serializable, like Streams.
  5. Use the RuleExecutionSetProvider to load RuleExecutionSets from serializable sources, like DOM Elements or Packages. Both the "ruleAdministrator.getLocalRuleExecutionSetProvider( null );" and the "ruleAdministrator.getRuleExecutionSetProvider( null );" (use null as a parameter).
  6. The example below shoes you how to register the LocalRuleExecutionSet:
    // Get the RuleAdministration
    RuleAdministrator ruleAdministrator = ruleServiceProvider.getRuleAdministrator();
    LocalRuleExecutionSetProvider ruleExecutionSetProvider =
      ruleAdministrator.getLocalRuleExecutionSetProvider( null );
    // Create a Reader for the drl
    URL drlUrl = new URL("http://mydomain.org/sources/myrules.drl");
    Reader drlReader = new InputStreamReader(  drlUrl.openStream()  );
    // Create the RuleExecutionSet for the drl
    RuleExecutionSet ruleExecutionSet =
      ruleExecutionSetProvider.createRuleExecutionSet( drlReader, null );
  7. You can use the "ruleExecutionSetProvider.createRuleExecutionSet( reader, null )" property to provide configuration for the incoming source. When null is passed the default is used to load the input as a drl. Allowed keys for a map are "source" and "dsl". The key "source" takes "drl" or "xml" as its value.
  8. Set "source" to "drl" to load a DRL, or to "xml" to load an XML source. "xml" will ignore any "dsl" key/value settings. The "dsl" key can take a Reader or a String (the contents of the dsl) as a value. See the following dsl example:
    // Get the RuleAdministration
    RuleAdministration ruleAdministrator = ruleServiceProvider.getRuleAdministrator();
    LocalRuleExecutionSetProvider ruleExecutionSetProvider =
      ruleAdministrator.getLocalRuleExecutionSetProvider( null );
    // Create a Reader for the drl
    URL drlUrl = new URL("http://mydomain.org/sources/myrules.drl");
    Reader drlReader = new InputStreamReader(  drlUrl.openStream()  );
    // Create a Reader for the dsl and a put in the properties map
    URL dslUrl = new URL("http://mydomain.org/sources/myrules.dsl");
    Reader dslReader = new InputStreamReader( dslUrl.openStream()  );
    Map properties = new HashMap();
    properties.put( "source", "drl" );
    properties.put( "dsl", dslReader );
    // Create the RuleExecutionSet for the drl and dsl
    RuleExecutionSet ruleExecutionSet =
      ruleExecutionSetProvider.createRuleExecutionSet( reader, properties );

17.12. Using Stateful and Stateless RuleSessions

Procedure 17.3. Task

  1. Get the runtime by accessing the RuleServiceProvider as shown:
    RuleRuntime ruleRuntime = ruleServiceProvider.getRuleRuntime();
  2. To create a rule session, use one of the two RuleRuntime public constants. These are "RuleRuntime.STATEFUL_SESSION_TYPE" and "RuleRuntime.STATELESS_SESSION_TYPE", accompanying the URI to the RuleExecutionSet you wish to instantiate a RuleSession for.
  3. Optionally, access the properties to specify globals.
  4. The createRuleSession(...) method will return a RuleSession instance. You should cast it to StatefulRuleSession or StatelessRuleSession:
    (StatefulRuleSession) session =
      ruleRuntime.createRuleSession( uri,
                                     RuleRuntime.STATEFUL_SESSION_TYPE );
    session.addObject( new PurchaseOrder( "cheese" ) );
  5. When using a StatelessRuleSession, you can only call executeRules(List list) passing a list of objects, and an optional filter, the resulting objects are then returned:
    (StatelessRuleSession) session =
      ruleRuntime.createRuleSession( uri,
                                     RuleRuntime.STATELESS_SESSION_TYPE );
    List list = new ArrayList();
    list.add( new PurchaseOrder( "even more cheese" ) );
    List results = new ArrayList();
    results = session.executeRules( list );

17.13. Using Globals with JSR94

JSR94 supports globals (in a manner that is not portable) by using the properties map passed to the RuleSession factory method. Globals must be defined in the DRL or XML file first, otherwise an exception will be thrown. The key represents the identifier declared in the DRL or XML, and the value is the instance you wish to be used in the execution.

17.14. Using Globals with JSR94 Example

Here is an example of implementing a global in JSR94:
java.util.List globalList = new java.util.ArrayList( );
java.util.Map map = new java.util.HashMap( );
map.put( "list", globalList ); 
//Open a stateless Session
StatelessRuleSession srs =
  (StatelessRuleSession) runtime.createRuleSession( "SistersRules",
                                                    RuleRuntime.STATELESS_SESSION_TYPE );
// Persons added to List
// call executeRules( ) giving a List of Objects as parameter
// There are rules which will put Objects in the List
// fetch the list from the map
List list = (java.util.List) map.get("list");
Do not forget to declare the global "list" in your DRL:
package SistersRules; 
import org.drools.jsr94.rules.Person; 
global java.util.List list
rule FindSisters 
    $person1 : Person ( $name1:name ) 
    $person2 : Person ( $name2:name ) 
    eval( $person1.hasSister($person2) ) 
    list.add($person1.getName() + " and " + $person2.getName() +" are sisters"); 
    assert( $person1.getName() + " and " + $person2.getName() +" are sisters"); 

17.15. Further Reading About JSR94

If you need more information on JSR94, please refer to the following links:
  1. Official JCP Specification for Java Rule Engine API (JSR 94)
  2. The Java Rule Engine API documentation
  3. The Logic From The Bottom Line: An Introduction to The Drools Project. By N. Alex Rupp, published on TheServiceSide.com in 2004
  4. Getting Started With the Java Rule Engine API (JSR 94): Toward Rule-Based Applications. By Dr. Qusay H. Mahmoud, published on Sun Developer Network in 2005
  5. Jess and the javax.rules API. By Ernest Friedman-Hill, published on TheServerSide.com in 2003

Chapter 18. JBoss Developer Studio

18.1. The Rules Integrated Development Environment (IDE)

The Integrated Development Environment (IDE) provides an environment to edit and test rules in various formats, then integrate them with applications.
The JBoss Rules IDE is delivered as an Eclipse plug-in, which allows you to author and manage rules from within Eclipse, as well as integrate rules with your application. This is an optional tool. The JBoss Rules IDE is also a part of the Red Hat Developer Studio (formerly known as JBoss IDE).

18.2. Rules IDE Features

The rules IDE has the following features:
  1. Textual/graphical rule editor
    1. An editor that is aware of DRL syntax, and provides content assistance (including an outline view)
    2. An editor that is aware of DSL (domain specific language) extensions, and provides content assistance.
  2. RuleFlow graphical editor
    You can edit visual graphs which represent a process (a rule flow). The RuleFlow can then be applied to your rule package to have imperative control.
  3. Wizards for fast creation of
    1. a "rules" project
    2. a rule resource, (a DRL file)
    3. a Domain Specific language
    4. a decision table
    5. a ruleflow
  4. A domain specific language editor
    1. Create and manage mappings from your user's language to the rule language
  5. Rule validation
    1. As rules are entered, the rule is "built" in the background and errors reported via the problem view where possible

18.3. JBoss Rules Runtimes

A JBoss Rules runtime is a collection of jar files that represents one specific release of the JBoss Rules project jars. To create a runtime, you must point the IDE to the release of your choice. You can also create a new runtime based on the latest JBoss Rules project jars included in the plugin itself. You are required to specify a default JBoss Rules runtime for your Eclipse workspace, but each individual project can override the default and select the appropriate runtime for that project specifically.

18.4. Defining a JBoss Rules Runtime

Procedure 18.1. Task

  1. Create a new session in JBoss Rules.
  2. Select Window Preferences. A "Preferences" dialog will appear.
  3. On the left side of this dialog, under the JBoss Rules category, select "Installed JBoss Rules runtimes". The panel on the right should then show the currently defined JBoss Rules runtimes.
  4. Click on the add button. A dialog will pop up asking for the name of your runtime and the location on your file system where it can be found.
  5. To use the default jar files from the JBoss Rules Eclipse plugin, create a new JBoss Rules runtime automatically by clicking the Create a new Drools 5 runtime ... button. A file browser will appear, asking you to select the folder on your file system where you want this runtime to be created. The plugin will then automatically copy all required dependencies to the specified folder.
  6. To use one specific release of the JBoss Rules project, create a folder on your file system that contains all the necessary JBoss Rules libraries and dependencies. Give your runtime a name and select the location of this folder containing all the required jars. Click OK.
  7. The runtime will appear in your table of installed JBoss Rules runtimes. Click on checkbox in front of the newly created runtime to make it the default JBoss Rules runtime. The default JBoss Rules runtime will be used as the runtime of all your JBoss Rules projects that have not selected a project-specific runtime.
  8. Restart Eclipse if you changed the default runtime and you want to make sure that all the projects that are using the default runtime update their classpath accordingly.

18.5. Selecting a Runtime for JBoss Rules Projects

Procedure 18.2. Task

  1. Use the New JBoss Rules Project wizard to create a new JBoss Rules Project.
  2. Alternatively, convert an existing Java project to a JBoss Rules project using the action by right-clicking on a Java object then clicking the Convert to JBoss Rules Project dialogue. The plugin will automatically add all the required jars to the classpath of your project.
  3. Optionally, on the last page of the New JBoss Rules Project wizard you can choose to have a project-specific runtime. Uncheck the Use default JBoss Rules runtime checkbox and select the appropriate runtime in the drop-down box.
  4. To access the preferences and add runtimes, go to the workspace preferences and click Configure workspace settings ....
  5. You can change the runtime of a JBoss Rules project at any time by opening the project properties and selecting the JBoss Rules category. Mark the Enable project specific settings checkbox and select the appropriate runtime from the drop-down box.
  6. Click the Configure workspace settings ... link. This opens the workspace preferences showing the currently installed runtimes. Use the menu to add new runtimes in this space. If you deselect the Enable project specific settings checkbox, it will use the default runtime as defined in your global preferences.

18.6. Example Rule Files

A newly created project contains an example rule file (Sample.drl) in the src/rules directory and an example Java file (DroolsTest.java) that can be used to execute the rules in a JBoss Rules engine. This is in the folder src/java, in the com.sample package. All the other jars that are necessary during execution are added to the classpath in a custom classpath container called JBoss Rules Library.

18.7. The JBoss Rules Builder

The JBoss Rules plug-in adds a JBoss Rules Builder capability to your Eclipse instance. This means you can enable a builder on any project that will build and validate your rules when resources change. This happens automatically with the Rule Project Wizard, but you can also enable it manually on any project. To fully validate the rules you will need to run them in a unit test of course.


If you have rule files with more than 500 rules per file, it may result in a slower performance. To counter this, turn off the builder or put the large rules into .rule files where you can still use the rule editor, but it won't build them in the background.

18.8. Creating a New Rule

Procedure 18.3. Task

  1. Create an empty text .drl file.
  2. Copy and paste your rule into it.
  3. Save and exit.
  4. Alternatively, use the Rules Wizard to create a rule but pressing Ctrl+N or by choosing it from the toolbar.
  5. The wizard will ask for some basic options for generating a rule resource. For storing rule files you would typically create a directory src/rules and create suitably named subdirectories. The package name is mandatory, and is similar to a package name in Java. (That is, it establishes a namespace for grouping related rules.)
  6. Select the options that suit you and click Finish.

You now have a rule skeleton which you can expand upon.

18.9. The Rule Editor

The rule editor is where rule managers and developers are modified. The rule editor follows the pattern of a normal text editor in Eclipse. It provides pop-up content assistance. You can invoke pop-up content assistance by pressing Ctrl+Space.
The rule editor works on files that have a .drl (or .rule) extension. Usually these contain related rules, but it would also be possible to have rules in individual files, grouped by being in the same package namespace. These DRL files are plain text files.

18.10. JBoss Rules Views

You can alternate between these views when modifying rules:
Working Memory View
Shows all elements in the JBoss Rules working memory.
Agenda View
Shows all elements on the agenda. For each rule on the agenda, the rule name and bound variables are shown.
Global Data View
Shows all global data currently defined in the JBoss Rules working memory.
Audit View
Can be used to display audit logs containing events that were logged during the execution of a rules engine, in tree form.
Rete View
This shows you the current Rete Network for your DRL file. You display it by clicking on the tab "Rete Tree" at the bottom of the DRL Editor window. With the Rete Network visualization being open, you can use drag-and-drop on individual nodes to arrange optimal network overview. You may also select multiple nodes by dragging a rectangle over them so the entire group can be moved around.


The Rete view works only in projects where the JBoss Rules Builder is set in the project´s properties. For other projects, you can use a workaround. Set up a JBoss Rule Project next to your current project and transfer the libraries and the DRLs you want to inspect with the Rete view. Click on the right tab below in the DRL Editor, then click "Generate Rete View".

18.11. Using JBoss Rules Views

Procedure 18.4. Task

  1. To be able to use JBoss Rules views, create breakpoints in your code by invoking the working memory. For example, the line where you call workingMemory.fireAllRules() is an ideal place to place a break.
  2. If the debugger halts at a joinpoint, select the working memory variable in the debug variables view. The available views can then be used to show the details of the selected working memory.

18.12. The Show Logical Structure

The Show Logical Structure is used with JBoss Rules views. It can toggle showing the logical structure of elements in the working memory or agenda items. Logical structures allow for example visualizing sets of elements in a more obvious way.

18.13. Creating Audit Logs

Procedure 18.5. Task

  1. To create an audit log, execute the rules engine. You will be given the option of creating a new audit log.
  2. Enter the following code:
    StatefulKnowledgeSession ksession = kbase.newStatefulKnowledgeSession();
    // Create a new Knowledge Runtime Logger, that logs to file.
    // An event.log file is created in the subdirectory log dir (which must exist) of the working directory
    KnowledgeRuntimeLogger logger = KnowledgeRuntimeLoggerFactory.newFileLogger( ksession, "log/event");
    // stop logging
  3. Open the log by clicking the Open Log action, the first icon in the Audit View, and select the file. The Audit View now shows all events that where logged during the executing of the rules.

18.14. Event Icons in Audit View

Table 18.1. Event Icons in Audit View

Icon Description
Green square Object has been inserted.
Yellow square Object has been updated.
Red square Object has been removed.
Right arrow Activation has been created.
Left arrow Activation has been canceled.
Blue diamond Activation has been executed.
Process icon Ruleflow has started or ended.
Activity icon Ruleflow-group activation or deactivation.
JBoss Rules icon Rule or rule package has been added or removed.

18.15. Methods for Retrieving Causes

If an event occurs when executing an activation, it is shown as a child of the activation's execution event. You can retrieve the cause in the following events::
  1. The cause of an object modified or retracted event is the last object event for that object. This is either the object asserted event, or the last object modified event for that object.
  2. The cause of an activation canceled or executed event is the corresponding activation created event.


When selecting an event, the cause is shown in green in the audit view. You can right-click the action and select the "Show Cause" menu item. This will scroll you to the cause of the selected event.

18.16. The DSL Editor

The DSL editor provides a tabular view of the mapping of Language to Rule Expressions. The Language Expression feeds the content assistance for the rule editor so that it can suggest Language Expressions from the DSL configuration. (The rule editor loads the DSL configuration when the rule resource is loaded for editing.

18.17. Rule Language Mapping

Rule language mapping defines the way which a language expression will be compiled by the rule engine compiler. The form of this rule language expression depends on whether it is intended for the condition or the action part of a rule. (For instance, in the RHS it may be a snippet of Java.) The scope item indicates where the expression belongs, the when item indicates the LHS, then the RHS, and the * item means it can go anywhere. It's also possible to create aliases for keywords.

18.18. Working with Rule Language Mapping

Procedure 18.6. Task

  1. Open the DSL editor and select the mapping tab.
  2. Select a mapping item (a row in the table) to see the expression and mapping in the text fields below the table.
  3. Double click or press the edit button to open the edit dialog.
  4. Other buttons let you remove and add mappings. Don't remove mappings while they are still in use.

18.19. DSL Translation Components

Table 18.2. DSL Translation Components

Name Duty
Parser The parser reads the rule text in a DSL line by line and tries to match some of the Language Expression. After a match, the values that correspond to a placeholder between curly braces (for example, {age}) are extracted from the rule source.
Placeholders The placeholders in the corresponding rule expression are replaced by their corresponding value. For example, a natural language expression maps to two constraints on a fact of type Person based on the fields age and location. The {age} and {location} values are then extracted from the original rule text.


If you do not wish to use a language mapping for a particular rule in a drl, prefix the expression with > and the compiler will not try to translate it according to the language definition. Also note that Domain Specific Languages are optional. When the rule is compiled, the .dsl file will also need to be available.

18.20. Tips for Working with Large DRL Files

  1. Depending on the JDK you use,you can increase the maximum size of the permanent generation. Do this by starting Eclipse with -XX:MaxPermSize=###m
  2. Rulesets of 4000 rules or greater should have the permanent generation set to at least 128Mb.
  3. You can put rules in a file with the .rule extension. The background builder will not try to compile them every time there is a change which will help the IDE run faster.

18.21. Creating Breakpoints

Procedure 18.7. Task

  1. To create breakpoints for easier debugging of rules, open the DRL editor and load the DRL file you wish to use.
  2. Double-click the ruler of the DRL editor at the line where you want to add a breakpoint. Note that rule breakpoints can only be created in the consequence of a rule. Double-clicking on a line where no breakpoint is allowed will do nothing. A breakpoint can be removed by double-clicking the ruler once more.
  3. Right-click the ruler. A popup menu will show up, containing the Toggle breakpoint action. Note that rule breakpoints can only be created in the consequence of a rule. The action is automatically disabled if no rule breakpoint is allowed at that line.
  4. Click the action to add a breakpoint at the selected line, or remove it if there was one already.


    The Debug Perspective contains a Breakpoints view which can be used to see all defined breakpoints, get their properties, enable/disable or remove them, and so on.

18.22. Debugging as a JBoss Rules Application

Procedure 18.8. Task

  1. Open the DRL Editor.
  2. Select the main class of your application.
  3. Right-click on it and select the Debug As > sub-menu and select JBoss Rules Application.
    Alternatively, you can also select the Debug ... menu item to open a new dialog for creating, managing and running debug configurations.
  4. Select the Drools Application item in the left tree and click the New launch configuration button (leftmost icon in the toolbar above the tree). This will create a new configuration with some of the properties already filled in based on the main class you selected in the beginning.
  5. Change the name of your debug configuration to something meaningful. You can accept the defaults for all other properties.
  6. Click the Debug button on the bottom to start debugging your application. You only have to define your debug configuration once. The next time you run your JBoss Rules application, you can select the previously defined configuration in the tree as a sub-element of the JBoss Rules tree node, and then click the JBoss Rules button. The Eclipse toolbar also contains shortcut buttons to quickly re-execute one of your previous configurations.

After clicking the Debug button, the application starts executing and will halt if any breakpoint is encountered. Whenever a JBoss Rules breakpoint is encountered, the corresponding DRL file is opened and the active line is highlighted. The Variables view also contains all rule parameters and their value. You can then use the default Java debug actions to decide what to do next: resume, terminate, step over, and so on. The debug view can also be used to inspect the contents of the Working Memory and the Agenda at that time as well. You don't have to select a Working Memory as the current executing working memory is automatically shown.

18.23. Rules IDE Preferences

The rules IDE comes with a set of customizable preferences that allow you to configure the following options:
Automatically reparse all rules if a Java resource is changed
Triggers a rebuilding of all the rules when a Java class is modified.
Allow cross reference in DRL files
Makes it possible to have a resource in a DRL file reference another resource defined in a different file. For example you could have a rule in a file using a type declared in another file. By enabling this option it will no longer possible to declare the same resource (that is, two rule with the same name in the same package) in two different DRL files.
Internal Drools classes use
Allows, disallows or discourages (generating warning) the use of JBoss Rules classes not exposed in the public API.

Chapter 19. Hello World Example

19.1. HelloWorld Example: Creating the KnowledgeBase and Session

final KnowledgeBuilder kbuilder = KnowledgeBuilderFactory.newKnowledgeBuilder();

// this will parse and compile in one step
        HelloWorldExample.class), ResourceType.DRL);

// Check the builder for errors
if (kbuilder.hasErrors()) {
    throw new RuntimeException("Unable to compile \"HelloWorld.drl\".");

// get the compiled packages (which are serializable)
final Collection<KnowledgePackage> pkgs = kbuilder.getKnowledgePackages();

// add the packages to a KnowledgeBase (deploy the knowledge packages).
final KnowledgeBase kbase = KnowledgeBaseFactory.newKnowledgeBase();

final StatefulKnowledgeSession ksession = kbase.newStatefulKnowledgeSession();
  • A KnowledgeBuilder is used to turn a DRL source file into Package objects which the Knowledge Base can consume.
  • The add method takes a Resource interface and a Resource Type as parameters. The Resource can be used to retrieve a DRL source file from various locations; in this case the DRL file is being retrieved from the classpath using a ResourceFactory, but it could come from a disk file or a URL.
  • Multiple packages of different namespaces can be added to the same Knowledge Base.
  • While the Knowledge Base will validate the package, it will only have access to the error information as a String, so if you wish to debug the error information you should do it on the KnowledgeBuilder instance.
  • Once the builder is error free, get the Package collection, instantiate a KnowledgeBase from the KnowledgeBaseFactory and add the package collection.

19.2. HelloWorld Example: Event Logging and Auditing

// setup the debug listeners
ksession.addEventListener( new DebugAgendaEventListener() );
ksession.addEventListener( new DebugWorkingMemoryEventListener() );
// setup the audit logging
KnowledgeRuntimeLogger logger =
  KnowledgeRuntimeLoggerFactory.newFileLogger(ksession, "log/helloworld");
  • Two default debug listeners are supplied: DebugAgendaEventListener and DebugWorkingMemoryEventListener. These print out debug event information to the System.err stream displayed in the Console window.
  • The KnowledgeRuntimeLogger provides execution auditing which can be viewed in a graphical viewer. This logger is a specialised implementation built on the Agenda and Working Memory listeners.
  • When the engine has finished executing, logger.close() must be called.

19.3. HelloWorld Example: Message Class

public static class Message {
    public static final int HELLO   = 0;
    public static final int GOODBYE = 1;

    private String          message;
    private int             status; 
  • The single class used in this example has two fields: the message, which is a String, and the status which can be one of the two integers HELLO or GOODBYE.

19.4. HelloWorld Example: Execution

final Message message = new Message();
message.setMessage("Hello World");



  • A single Message object is created with the message text "Hello World" and the status HELLO and then inserted into the engine, at which point fireAllRules() is executed.
  • All network evaluation is done during the insert time. By the time the program execution reaches the fireAllRules() method call the engine already knows which rules are fully matches and able to fire.


To execute the example as a Java application:
  1. Open the class org.drools.examples.helloworld.HelloWorldExample in your Eclipse IDE.
  2. Right-click the class and select Run as... and then Java application

19.5. HelloWorld Example: System.out in the Console Window

==>[ActivationCreated(0): rule=Hello World; 
[ObjectInserted: handle=[fid:1:1:org.drools.examples.helloworld.HelloWorldExample$Message@17cec96];
[BeforeActivationFired: rule=Hello World; 
==>[ActivationCreated(4): rule=Good Bye; 
[ObjectUpdated: handle=[fid:1:2:org.drools.examples.helloworld.HelloWorldExample$Message@17cec96];
[AfterActivationFired(0): rule=Hello World]
[BeforeActivationFired: rule=Good Bye; 
[AfterActivationFired(4): rule=Good Bye]
  • By putting a breakpoint on the fireAllRules() method and select the ksession variable, you can see that the "Hello World" rule is already activated and on the Agenda, confirming that all the pattern matching work was already done during the insert.
  • The application print outs go to System.out while the debug listener print outs go to System.err.

19.6. HelloWorld Example: Rule "Hello World"

rule "Hello World"
      dialect "mvel"
      m : Message( status == Message.HELLO, message : message )
      System.out.println( message ); 
      modify ( m ) { message = "Goodbye cruel world",
                     status = Message.GOODBYE };
  • The LHS (after when) section of the rule states that it will be activated for each Message object inserted into the Working Memory whose status is Message.HELLO.
  • Two variable bindings are created: the variable message is bound to the message attribute and the variable m is bound to the matched Message object itself.
  • The RHS (after then) or consequence part of the rule is written using the MVEL expression language, as declared by the rule's attribute dialect.
  • After printing the content of the bound variable message to System.out, the rule changes the values of the message and status attributes of the Message object bound to m.
  • MVEL's modify statement allows you to apply a block of assignments in one statement, with the engine being automatically notified of the changes at the end of the block.

19.7. HelloWorld Example: Using the "Debug as..." Option

Procedure 19.1. Task

  1. To access this debugging option, open the class org.drools.examples.HelloWorld in your Eclipse IDE.
  2. Right-click the class and select "Debug as..." and then "Drools application". The rule will be shown along with information about where it is.

19.8. HelloWorld Example: Rule "Good Bye"

rule "Good Bye"
      dialect "java"
      Message( status == Message.GOODBYE, message : message )
      System.out.println( message ); 
  • The "Good Bye" rule, which specifies the "java" dialect, is similar to the "Hello World" rule except that it matches Message objects whose status is Message.GOODBYE

Chapter 20. Salience State Example

20.1. Salience State Example: State Class Example

public class State {
    public static final int NOTRUN   = 0;
    public static final int FINISHED = 1;

    private final PropertyChangeSupport changes =
        new PropertyChangeSupport( this );

    private String name;
    private int    state;

    ... setters and getters go here...
  • Each State class has fields for its name and its current state (see the class org.drools.examples.state.State). The two possible states for each objects are NOTRUN and FINISHED.

20.2. Salience State Example: Execution

State a = new State( "A" );
State b = new State( "B" );
State c = new State( "C" );
final State d = new State( "D" );

// By setting dynamic to TRUE, Drools will use JavaBean
// PropertyChangeListeners so you don't have to call modify or update().
boolean dynamic = true;

session.insert( a, dynamic );
session.insert( b, dynamic );
session.insert( c, dynamic );
session.insert( d, dynamic );

session.dispose(); // Stateful rule session must always be disposed when finished
  • Each instance is asserted in turn into the Session and then fireAllRules() is called.

20.3. Salience State Example: Executing Applications

Procedure 20.1. Task

  1. Open the class org.drools.examples.state.StateExampleUsingSalience in the Eclipse IDE.
  2. Right-click the class and select Run as... and then Java application. The following output will appear:
    A finished
    B finished
    C finished
    D finished

20.4. Salience State Example: Using Audit Logging with Operations

Procedure 20.2. Task

  1. To view the Audit log generated by an operation, open the IDE and click on Window and then select Show View, then Other..., Drools and Audit View.
  2. In the "Audit View" click the Open Log button and select the file <drools-examples-dir>/log/state.log.

20.5. Salience State Example: Rule "Bootstrap"

rule Bootstrap
        a : State(name == "A", state == State.NOTRUN )
        System.out.println(a.getName() + " finished" );
        a.setState( State.FINISHED );
rule "A to B"
        State(name == "A", state == State.FINISHED )
        b : State(name == "B", state == State.NOTRUN )
        System.out.println(b.getName() + " finished" );
        b.setState( State.FINISHED );
  • Every action and the corresponding changes appear in the Working Memory.
  • The assertion of the State object A in the state NOTRUN activates the Bootstrap rule, while the assertions of the other State objects have no immediate effect.
  • The execution of rule Bootstrap changes the state of A to FINISHED, which, in turn, activates rule "A to B".

20.6. Salience State Example: Rule "B to C"

rule "B to C"
        salience 10
        State(name == "B", state == State.FINISHED )
        c : State(name == "C", state == State.NOTRUN )
        System.out.println(c.getName() + " finished" );
        c.setState( State.FINISHED );
  • The conflict resolution strategy allows the engine's Agenda to decide which rule to fire.
  • As rule "B to C" has the higher salience value (10 versus the default salience value of 0), it fires first, modifying object C to state FINISHED.
  • The Agenda view can also be used to investigate the state of the Agenda, with debug points being placed in the rules themselves and the Agenda view opened.

20.7. Salience State Example: Rule "B to D"

rule "B to D"
        State(name == "B", state == State.FINISHED )
        d : State(name == "D", state == State.NOTRUN )
        System.out.println(d.getName() + " finished" );
        d.setState( State.FINISHED );
  • Rule "B to D" fires last, modifying object D to state FINISHED.
  • There are no more rules to execute and so the engine stops.

20.8. Salience State Example: Inserting a Dynamic Fact

// By setting dynamic to TRUE, JBoss Rules will use JavaBean
// PropertyChangeListeners so you don't have to call modify or update().
final boolean dynamic = true;

session.insert( fact, dynamic );
  • For the engine to see and react to changes of fact properties, the application must tell the engine that changes occurred. This can be done explicitly in the rules by using the modify statement, or implicitly by letting the engine know that the facts implement PropertyChangeSupport as defined by the JavaBeans specification.
  • The above example demonstrates how to use PropertyChangeSupport to avoid the need for explicit modify statements in the rules.
  • Ensure that your facts implement PropertyChangeSupport, the same way the class org.drools.example.State does.

20.9. Salience State Example: Setter with PropertyChangeSupport

public void setState(final int newState) {
    int oldState = this.state;
    this.state = newState;
    this.changes.firePropertyChange( "state",
                                     newState );
  • The setter for state in the class org.drools.examples.
  • When using PropertyChangeListener objects, each setter must implement a little extra code for the notification.

20.10. Salience State Example: Agenda Group Rules "B to C"

rule "B to C"
      agenda-group "B to C"
      auto-focus true       
      State(name == "B", state == State.FINISHED )      
      c : State(name == "C", state == State.NOTRUN )
      System.out.println(c.getName() + " finished" );
      c.setState( State.FINISHED );
      kcontext.getKnowledgeRuntime().getAgenda().getAgendaGroup( "B to D" ).setFocus();
rule "B to D"
      agenda-group "B to D"
      State(name == "B", state == State.FINISHED )      
      d : State(name == "D", state == State.NOTRUN )
      System.out.println(d.getName() + " finished" );
      d.setState( State.FINISHED );
  • By default, all rules are in the agenda group "MAIN".
  • The "agenda-group" attribute lets you specify a different agenda group for the rule. Initially, a Working Memory has its focus on the Agenda group "MAIN".
  • A group's rules will only fire when the group receives the focus. This can be achieved either by using the method setFocus() or the rule attribute auto-focus.
  • auto-focus means that the rule automatically sets the focus to its agenda group when the rule is matched and activated. It is this "auto-focus" that enables rule "B to C" to fire before "B to D".
  • The rule "B to C" calls setFocus() on the agenda group "B to D", allowing its active rules to fire, which allows the rule "B to D" to fire.

20.11. Salience State Example: Agenda Group Rules "B to D"

rule "B to D"
      agenda-group "B to D"
      State(name == "B", state == State.FINISHED )      
      d : State(name == "D", state == State.NOTRUN )
      System.out.println(d.getName() + " finished" );
      d.setState( State.FINISHED );

20.12. Salience State Example: Agenda Group Rules "D to E"

rule "D to E"
      State(name == "D", state == State.FINISHED )      
      e : State(name == "E", state == State.NOTRUN )
      System.out.println(e.getName() + " finished" );
      e.setState( State.FINISHED );
This produces the following expected output:
A finished
B finished
C finished
D finished
E finished
  • StateExampleWithDynamicRules adds another rule to the Rule Base after fireAllRules().

Chapter 21. Fibonacci Example

21.1. Fibonacci Example: The Class

public static class Fibonacci {
    private int  sequence;
    private long value;

    public Fibonacci( final int sequence ) {
        this.sequence = sequence;
        this.value = -1;

    ... setters and getters go here...
  • The sequence field is used to indicate the position of the object in the Fibonacci number sequence.
  • The value field shows the value of that Fibonacci object for that sequence position, using -1 to indicate a value that still needs to be computed.

21.2. Fibonacci Example: Execution

Procedure 21.1. Task

  1. Launch the Eclipse IED.
  2. Open the class org.drools.examples.fibonacci.FibonacciExample.
  3. Right-click the class and select Run as... and then Java application.

Eclipse shows the following output in its console window (with "...snip..." indicating lines that were removed to save space):

recurse for 50
recurse for 49
recurse for 48
recurse for 47
recurse for 5
recurse for 4
recurse for 3
recurse for 2
1 == 1
2 == 1
3 == 2
4 == 3
5 == 5
6 == 8
47 == 2971215073
48 == 4807526976
49 == 7778742049
50 == 12586269025

21.3. Fibonacci Example: Execution Details

ksession.insert( new Fibonacci( 50 ) );
  • To use this with Java, a single Fibonacci object is inserted with a sequence field of 50.
  • A recursive rule is used to insert the other 49 Fibonacci objects.
  • This example uses the MVEL dialect. This means you can use the modify keyword, which allows a block setter action which also notifies the engine of changes.

21.4. Fibonacci Example: Recurse Rule

rule Recurse
    salience 10
        f : Fibonacci ( value == -1 )
        not ( Fibonacci ( sequence == 1 ) )
        insert( new Fibonacci( f.sequence - 1 ) );
        System.out.println( "recurse for " + f.sequence );
  • The Recurse rule matches each asserted Fibonacci object with a value of -1, creating and asserting a new Fibonacci object with a sequence of one less than the currently matched object.
  • Each time a Fibonacci object is added while the one with a sequence field equal to 1 does not exist, the rule re-matches and fires again.
  • The not conditional element is used to stop the rule's matching once we have all 50 Fibonacci objects in memory.
  • The Recurse rule has a salience value so all 50 Fibonacci objects are asserted before the Bootstrap rule is executed.
  • You can switch to the Audit view to show the original assertion of the Fibonacci object with a sequence field of 50, done with Java code. From there on, the Audit view shows the continual recursion of the rule, where each asserted Fibonacci object causes the Recurse rule to become activated and to fire again.

21.5. Fibonacci Example: Bootstrap Rule

rule Bootstrap
        f : Fibonacci( sequence == 1 || == 2, value == -1 ) // multi-restriction
        modify ( f ){ value = 1 };
        System.out.println( f.sequence + " == " + f.value );
  • When a Fibonacci object with a sequence field of 2 is asserted the Bootstrap rule is matched and activated along with the Recurse rule.
  • Note the multi-restriction on field sequence, testing for equality with 1 or 2.
  • When a Fibonacci object with a sequence of 1 is asserted the Bootstrap rule is matched again, causing two activations for this rule. The Recurse rule does not match and activate because the not conditional element stops the rule's matching as soon as a Fibonacci object with a sequence of 1 exists.

21.6. Fibonacci Example: Calculate Rule

rule Calculate
        // Bind f1 and s1
        f1 : Fibonacci( s1 : sequence, value != -1 )
        // Bind f2 and v2; refer to bound variable s1
        f2 : Fibonacci( sequence == (s1 + 1), v2 : value != -1 )
        // Bind f3 and s3; alternative reference of f2.sequence
        f3 : Fibonacci( s3 : sequence == (f2.sequence + 1 ), value == -1 )      
        // Note the various referencing techniques.
        modify ( f3 ) { value = f1.value + v2 };
        System.out.println( s3 + " == " + f3.value );
  • When there are two Fibonacci objects with values not equal to -1, the Calculate rule is able to match them.
  • There are 50 Fibonacci objects in the Working Memory. A suitable triple should be selected to calculate each of value in turn.
  • Using three Fibonacci patterns in a rule without field constraints to confine the possible cross products would result in many incorrect rule firings. The Calculate rule uses field constraints to correctly constraint the Fibonacci patterns in the correct order. This technique is called cross product matching.
  • The first pattern finds any Fibonacci with a value != -1 and binds both the pattern and the field. The second Fibonacci does this too, but it adds an additional field constraint to ensure that its sequence is greater by one than the Fibonacci bound to f1. When this rule fires for the first time, the two constraints ensure that f1 references sequence 1 and f2 references sequence 2. The final pattern finds the Fibonacci with a value equal to -1 and with a sequence one greater than f2.
  • There are three Fibonacci objects correctly selected from the available cross products. You can calculate the value for the third Fibonacci object that's bound to f3.
  • The modify statement updates the value of the Fibonacci object bound to f3. This means there is now another new Fibonacci object with a value not equal to -1, which allows the Calculate rule to rematch and calculate the next Fibonacci number.
  • Switching to the Audit view will show how the firing of the last Bootstrap modifies the Fibonacci object, enabling the "Calculate" rule to match. This then modifies another Fibonacci object allowing the Calculate rule to match again. This continues till the value is set for all Fibonacci objects.

Chapter 22. Banking Example

22.1. Banking Example: RuleRunner

public class RuleRunner {

    public RuleRunner() {

    public void runRules(String[] rules,
                         Object[] facts) throws Exception {

        KnowledgeBase kbase = KnowledgeBaseFactory.newKnowledgeBase();
        KnowledgeBuilder kbuilder = KnowledgeBuilderFactory.newKnowledgeBuilder();

        for ( int i = 0; i < rules.length; i++ ) {
            String ruleFile = rules[i];
            System.out.println( "Loading file: " + ruleFile );
            kbuilder.add( ResourceFactory.newClassPathResource( ruleFile,
                                                                RuleRunner.class ),
                          ResourceType.DRL );

        Collection<KnowledgePackage> pkgs = kbuilder.getKnowledgePackages();
        kbase.addKnowledgePackages( pkgs );
        StatefulKnowledgeSession ksession = kbase.newStatefulKnowledgeSession();

        for ( int i = 0; i < facts.length; i++ ) {
            Object fact = facts[i];
            System.out.println( "Inserting fact: " + fact );
            ksession.insert( fact );

  • The class RuleRunner is used to execute one or more DRL files against a set of data. It compiles the Packages and creates the Knowledge Base for each execution, allowing us to easily execute each scenario and inspect the outputs.

22.2. Banking Example: Rule in Example1.drl

rule "Rule 01"   
        eval( 1==1 )
        System.out.println( "Rule 01 Works" );
Loading file: Example1.drl
Rule 01 Works
  • This rule has a single eval condition that will always be true, so that this rule will match and fire after it has been started.
  • The output shows the rule matches and executes the single print statement.

22.3. Banking Example: Java Example 2

public class Example2 {
    public static void main(String[] args) throws Exception {
        Number[] numbers = new Number[] {wrap(3), wrap(1), wrap(4), wrap(1), wrap(5)};
        new RuleRunner().runRules( new String[] { "Example2.drl" },
                                   numbers );
    private static Integer wrap( int i ) {
        return new Integer(i);
  • This example asserts basic facts and prints them out.

22.4. Banking Example: Rule in Example2.drl

rule "Rule 02"
        Number( $intValue : intValue )
        System.out.println( "Number found with value: " + $intValue ); 
Loading file: Example2.drl
Inserting fact: 3
Inserting fact: 1
Inserting fact: 4
Inserting fact: 1
Inserting fact: 5
Number found with value: 5
Number found with value: 1
Number found with value: 4
Number found with value: 1
Number found with value: 3
  • This is a basic rule for printing out the specified numbers. It identifies any facts that are Number objects and prints out the values. Notice the use of the abstract class Number.
  • The pattern matching engine is able to match interfaces and superclasses of asserted objects.
  • The output shows the DRL being loaded, the facts inserted and then the matched and fired rules. You can see that each inserted number is matched and fired and thus printed.

22.5. Banking Example: Example3.java

public class Example3 {
    public static void main(String[] args) throws Exception {
        Number[] numbers = new Number[] {wrap(3), wrap(1), wrap(4), wrap(1), wrap(5)};
        new RuleRunner().runRules( new String[] { "Example3.drl" },
                                   numbers );
    private static Integer wrap(int i) {
        return new Integer(i);
  • This is a basic rule-based sorting technique.

22.6. Banking Example: Rule in Example3.drl

rule "Rule 03"
        $number : Number( )
        not Number( intValue < $number.intValue )
        System.out.println("Number found with value: " + $number.intValue() ); 
        retract( $number );
Loading file: Example3.drl
Inserting fact: 3
Inserting fact: 1
Inserting fact: 4
Inserting fact: 1
Inserting fact: 5
Number found with value: 1
Number found with value: 1
Number found with value: 3
Number found with value: 4
Number found with value: 5
  • The first line of the rule identifies a Number and extracts the value.
  • The second line ensures that there does not exist a smaller number than the one found by the first pattern. The retraction of the number after it has been printed means that the smallest number has been removed, revealing the next smallest number, and so on.

22.7. Banking Example: Class Cashflow

public class Cashflow {
    private Date   date;
    private double amount;

    public Cashflow() {

    public Cashflow(Date date, double amount) {
        this.date = date;
        this.amount = amount;

    public Date getDate() {
        return date;

    public void setDate(Date date) {
        this.date = date;

    public double getAmount() {
        return amount;

    public void setAmount(double amount) {
        this.amount = amount;

    public String toString() {
        return "Cashflow[date=" + date + ",amount=" + amount + "]";
  • Class Cashflow has two simple attributes, a date and an amount. (Using the type double for monetary units is generally bad practice because floating point numbers cannot represent most numbers accurately.)
  • There is an overloaded constructor to set the values and a method toString to print a cashflow.

22.8. Banking Example: Example4.java

public class Example4 {
    public static void main(String[] args) throws Exception {
        Object[] cashflows = {
            new Cashflow(new SimpleDate("01/01/2007"), 300.00),
            new Cashflow(new SimpleDate("05/01/2007"), 100.00),
            new Cashflow(new SimpleDate("11/01/2007"), 500.00),
            new Cashflow(new SimpleDate("07/01/2007"), 800.00),
            new Cashflow(new SimpleDate("02/01/2007"), 400.00),
        new RuleRunner().runRules( new String[] { "Example4.drl" },
                                   cashflows );
  • The Java code in this example inserts five Cashflow objects, with varying dates and amounts.

22.9. Banking Example: Class SimpleDate

public class SimpleDate extends Date {
    private static final SimpleDateFormat format = new SimpleDateFormat("dd/MM/yyyy");
    public SimpleDate(String datestr) throws Exception {             
  • The convenience class SimpleDate extends java.util.Date, providing a constructor taking a String as input and defining a date format.

22.10. Banking Example: Rule in Example4.drl

rule "Rule 04"   
        $cashflow : Cashflow( $date : date, $amount : amount )
        not Cashflow( date < $date)
        System.out.println("Cashflow: "+$date+" :: "+$amount);  
Loading file: Example4.drl
Inserting fact: Cashflow[date=Mon Jan 01 00:00:00 GMT 2007,amount=300.0]
Inserting fact: Cashflow[date=Fri Jan 05 00:00:00 GMT 2007,amount=100.0]
Inserting fact: Cashflow[date=Thu Jan 11 00:00:00 GMT 2007,amount=500.0]
Inserting fact: Cashflow[date=Sun Jan 07 00:00:00 GMT 2007,amount=800.0]
Inserting fact: Cashflow[date=Tue Jan 02 00:00:00 GMT 2007,amount=400.0]
Cashflow: Mon Jan 01 00:00:00 GMT 2007 :: 300.0
Cashflow: Tue Jan 02 00:00:00 GMT 2007 :: 400.0
Cashflow: Fri Jan 05 00:00:00 GMT 2007 :: 100.0
Cashflow: Sun Jan 07 00:00:00 GMT 2007 :: 800.0
Cashflow: Thu Jan 11 00:00:00 GMT 2007 :: 500.0
  • A Cashflow is identified and the date and amount are extracted.
  • In the second line of the rule in it is determined that there is no Cashflow with an earlier date than the one found.
  • In the consequence, the Cashflow is printed. This satisfies the rule and then retracts it, making way for the next earliest Cashflow.

22.11. Banking Example: Class TypedCashflow

public class TypedCashflow extends Cashflow {
    public static final int CREDIT = 0;
    public static final int DEBIT  = 1;

    private int             type;

    public TypedCashflow() {

    public TypedCashflow(Date date, int type, double amount) {
        super( date, amount );
        this.type = type;

    public int getType() {
        return type;

    public void setType(int type) {
        this.type = type;

    public String toString() {
        return "TypedCashflow[date=" + getDate() +
               ",type=" + (type == CREDIT ? "Credit" : "Debit") +
               ",amount=" + getAmount() + "]";
  • When the Cashflow is extended it results in a TypedCashflow, which can be a credit or a debit operation.

22.12. Banking Example: Example5.java

public class Example5 {
    public static void main(String[] args) throws Exception {      
        Object[] cashflows = {
            new TypedCashflow(new SimpleDate("01/01/2007"),    
                              TypedCashflow.CREDIT, 300.00),
            new TypedCashflow(new SimpleDate("05/01/2007"),
                              TypedCashflow.CREDIT, 100.00),
            new TypedCashflow(new SimpleDate("11/01/2007"),
                              TypedCashflow.CREDIT, 500.00),
            new TypedCashflow(new SimpleDate("07/01/2007"),
                              TypedCashflow.DEBIT, 800.00),
            new TypedCashflow(new SimpleDate("02/01/2007"),
                              TypedCashflow.DEBIT, 400.00),
        new RuleRunner().runRules( new String[] { "Example5.drl" },
                                   cashflows );
rule "Rule 05"  
        $cashflow : TypedCashflow( $date : date,
                                   $amount : amount,
                                   type == TypedCashflow.CREDIT )
        not TypedCashflow( date < $date,
                           type == TypedCashflow.CREDIT )
        System.out.println("Credit: "+$date+" :: "+$amount);   
Loading file: Example5.drl
Inserting fact: TypedCashflow[date=Mon Jan 01 00:00:00 GMT 2007,type=Credit,amount=300.0]
Inserting fact: TypedCashflow[date=Fri Jan 05 00:00:00 GMT 2007,type=Credit,amount=100.0]
Inserting fact: TypedCashflow[date=Thu Jan 11 00:00:00 GMT 2007,type=Credit,amount=500.0]
Inserting fact: TypedCashflow[date=Sun Jan 07 00:00:00 GMT 2007,type=Debit,amount=800.0]
Inserting fact: TypedCashflow[date=Tue Jan 02 00:00:00 GMT 2007,type=Debit,amount=400.0]
Credit: Mon Jan 01 00:00:00 GMT 2007 :: 300.0
Credit: Fri Jan 05 00:00:00 GMT 2007 :: 100.0
Credit: Thu Jan 11 00:00:00 GMT 2007 :: 500.0
  • Both the class and the .drl are supplied to the rule engine.
  • In the class, a set of Cashflow objects are created which are either credit or debit operations.
  • A Cashflow fact is identified with a type of CREDIT and extract the date and the amount. In the second line of the rule we ensure that there is no Cashflow of the same type with an earlier date than the one found. In the consequence, we print the cashflow satisfying the patterns and then retract it, making way for the next earliest cashflow of type

22.13. Banking Example: Class Account

public class Account {
    private long   accountNo;
    private double balance = 0;

    public Account() {

    public Account(long accountNo) {
        this.accountNo = accountNo;

    public long getAccountNo() {
        return accountNo;

    public void setAccountNo(long accountNo) {
        this.accountNo = accountNo;

    public double getBalance() {
        return balance;

    public void setBalance(double balance) {
        this.balance = balance;

    public String toString() {
        return "Account[" + "accountNo=" + accountNo + ",balance=" + balance + "]";
  • Two separate Account objects are created and injected into the Cashflows objects before being passed to the Rule Engine.

22.14. Banking Example: Class AllocatedCashflow

public class AllocatedCashflow extends TypedCashflow {
    private Account account;

    public AllocatedCashflow() {

    public AllocatedCashflow(Account account, Date date, int type, double amount) {
        super( date, type, amount );
        this.account = account;

    public Account getAccount() {
        return account;

    public void setAccount(Account account) {
        this.account = account;

    public String toString() {
        return "AllocatedCashflow[" +
               "account=" + account +
               ",date=" + getDate() + 
               ",type=" + (getType() == CREDIT ? "Credit" : "Debit") + 
               ",amount=" + getAmount() + "]";
  • Extending the TypedCashflow, results in AllocatedCashflow, which includes an Account reference.

22.15. Banking Example: Extending Example5.java

public class Example6 {
    public static void main(String[] args) throws Exception {      
        Account acc1 = new Account(1);
        Account acc2 = new Account(2);
        Object[] cashflows = {
            new AllocatedCashflow(acc1,new SimpleDate("01/01/2007"),
                                  TypedCashflow.CREDIT, 300.00),
            new AllocatedCashflow(acc1,new SimpleDate("05/02/2007"),
                                  TypedCashflow.CREDIT, 100.00),
            new AllocatedCashflow(acc2,new SimpleDate("11/03/2007"),
                                  TypedCashflow.CREDIT, 500.00),
            new AllocatedCashflow(acc1,new SimpleDate("07/02/2007"),
                                  TypedCashflow.DEBIT,  800.00),
            new AllocatedCashflow(acc2,new SimpleDate("02/03/2007"),
                                  TypedCashflow.DEBIT,  400.00),
            new AllocatedCashflow(acc1,new SimpleDate("01/04/2007"),    
                                  TypedCashflow.CREDIT, 200.00),
            new AllocatedCashflow(acc1,new SimpleDate("05/04/2007"),
                                  TypedCashflow.CREDIT, 300.00),
            new AllocatedCashflow(acc2,new SimpleDate("11/05/2007"),
                                  TypedCashflow.CREDIT, 700.00),
            new AllocatedCashflow(acc1,new SimpleDate("07/05/2007"),
                                  TypedCashflow.DEBIT,  900.00),
            new AllocatedCashflow(acc2,new SimpleDate("02/05/2007"),
                                  TypedCashflow.DEBIT,  100.00)           
        new RuleRunner().runRules( new String[] { "Example6.drl" },
                                   cashflows );
  • This Java code creates two Account objects and passes one of them into each cashflow in the constructor call.

22.16. Banking Example: Rule in Example6.drl

rule "Rule 06 - Credit"  
        $cashflow : AllocatedCashflow( $account : account,
                                       $date : date,
                                       $amount : amount,
                                       type == TypedCashflow.CREDIT )
        not AllocatedCashflow( account == $account, date < $date)
        System.out.println("Credit: " + $date + " :: " + $amount);     
        System.out.println("Account: " + $account.getAccountNo() +
                           " - new balance: " + $account.getBalance());          

rule "Rule 06 - Debit"  
        $cashflow : AllocatedCashflow( $account : account,
                            $date : date,
                            $amount : amount,
                            type == TypedCashflow.DEBIT )
        not AllocatedCashflow( account == $account, date < $date)
        System.out.println("Debit: " + $date + " :: " + $amount);      
        $account.setBalance($account.getBalance() - $amount);
        System.out.println("Account: " + $account.getAccountNo() +
                           " - new balance: " + $account.getBalance());           
Loading file: Example6.drl
Inserting fact: AllocatedCashflow[account=Account[accountNo=1,balance=0.0],date=Mon Jan 01 00:00:00 GMT 2007,type=Credit,amount=300.0]
Inserting fact: AllocatedCashflow[account=Account[accountNo=1,balance=0.0],date=Mon Feb 05 00:00:00 GMT 2007,type=Credit,amount=100.0]
Inserting fact: AllocatedCashflow[account=Account[accountNo=2,balance=0.0],date=Sun Mar 11 00:00:00 GMT 2007,type=Credit,amount=500.0]
Inserting fact: AllocatedCashflow[account=Account[accountNo=1,balance=0.0],date=Wed Feb 07 00:00:00 GMT 2007,type=Debit,amount=800.0]
Inserting fact: AllocatedCashflow[account=Account[accountNo=2,balance=0.0],date=Fri Mar 02 00:00:00 GMT 2007,type=Debit,amount=400.0]
Inserting fact: AllocatedCashflow[account=Account[accountNo=1,balance=0.0],date=Sun Apr 01 00:00:00 BST 2007,type=Credit,amount=200.0]
Inserting fact: AllocatedCashflow[account=Account[accountNo=1,balance=0.0],date=Thu Apr 05 00:00:00 BST 2007,type=Credit,amount=300.0]
Inserting fact: AllocatedCashflow[account=Account[accountNo=2,balance=0.0],date=Fri May 11 00:00:00 BST 2007,type=Credit,amount=700.0]
Inserting fact: AllocatedCashflow[account=Account[accountNo=1,balance=0.0],date=Mon May 07 00:00:00 BST 2007,type=Debit,amount=900.0]
Inserting fact: AllocatedCashflow[account=Account[accountNo=2,balance=0.0],date=Wed May 02 00:00:00 BST 2007,type=Debit,amount=100.0]
Debit: Fri Mar 02 00:00:00 GMT 2007 :: 400.0
Account: 2 - new balance: -400.0
Credit: Sun Mar 11 00:00:00 GMT 2007 :: 500.0
Account: 2 - new balance: 100.0
Debit: Wed May 02 00:00:00 BST 2007 :: 100.0
Account: 2 - new balance: 0.0
Credit: Fri May 11 00:00:00 BST 2007 :: 700.0
Account: 2 - new balance: 700.0
Credit: Mon Jan 01 00:00:00 GMT 2007 :: 300.0
Account: 1 - new balance: 300.0
Credit: Mon Feb 05 00:00:00 GMT 2007 :: 100.0
Account: 1 - new balance: 400.0
Debit: Wed Feb 07 00:00:00 GMT 2007 :: 800.0
Account: 1 - new balance: -400.0
Credit: Sun Apr 01 00:00:00 BST 2007 :: 200.0
Account: 1 - new balance: -200.0
Credit: Thu Apr 05 00:00:00 BST 2007 :: 300.0
Account: 1 - new balance: 100.0
Debit: Mon May 07 00:00:00 BST 2007 :: 900.0
Account: 1 - new balance: -800.0
  • In this example, each cashflow in date order is applied and calculated, resulting in a print of the balance.
  • Although there are separate rules for credits and debits, there is no type specified when checking for earlier cashflows. This is so that all cashflows are applied in date order, regardless of the cashflow type.
  • In the conditions the account has identified and in the consequences, the cashflow amount is updated.

Chapter 23. Pricing Rule Example

23.1. Pricing Rule Example: Executing the Pricing Rule Example

Procedure 23.1. Task

  1. Open your console.
  2. Open the file PricingRuleDTExample.java and execute it as a Java application. It will produce the following output in the console window:
    Cheapest possible
    BASE PRICE IS: 120
  3. Use the following code to execute the example:
    DecisionTableConfiguration dtableconfiguration =
            dtableconfiguration.setInputType( DecisionTableInputType.XLS );
            KnowledgeBuilder kbuilder = KnowledgeBuilderFactory.newKnowledgeBuilder();
            Resource xlsRes = ResourceFactory.newClassPathResource( "ExamplePolicyPricing.xls",
                                                                    getClass() );
            kbuilder.add( xlsRes,
                          dtableconfiguration );
    The DecisionTableConfiguration object's type is set to DecisionTableInputType.XLS.
    There are two fact types used in this example, Driver and Policy. Both are used with their default values. The Driver is 30 years old, has had no prior claims and currently has a risk profile of LOW. The Policy being applied for is COMPREHENSIVE, and it has not yet been approved.

23.2. Pricing Rule Example: Decision Table Configuration

Decision Table Configuration

Figure 23.1. Decision Table Configuration

  • The RuleSet declaration provides the package name. There are also other optional items you can put here, such as Variables for global variables, and Imports for importing classes. In this case, the namespace of the rules is the same as the fact classes and thus can be omitted.
  • The name after the RuleTable declaration (Pricing bracket) is used as the prefix for all the generated rules.
  • "CONDITION or ACTION", indicates the purpose of the column, that is, whether it forms part of the condition or the consequence of the rule that will be generated.
  • The driver's data is spread across three cells which means that the template expressions below it are applied. You can observe the driver's age range (which uses $1 and $2 with comma-separated values), locationRiskProfile, and priorClaims in the respective columns.
  • You can set a policy base price and message log in the Action column.

23.3. Pricing Rule Example: Base Price Calculation Example

Base Price Calculation Example

Figure 23.2. Base Price Calculation Example

  • Broad category brackets are indicated by the comment in the leftmost column.
  • The details of the drivers match row number 18 as they have no prior accidents and are 30 years old. This gives us a base price of 120.

23.4. Pricing Rule Example: Discount Calculation Example

Discount Calculation Example

Figure 23.3. Discount Calculation Example

  • The discount results from the Age bracket, the number of prior claims, and the policy type.
  • The driver is 30 with no prior claims and is applying for a COMPREHENSIVE policy. This means a 20% discount can be applied. Note that this is actually a separate table in the same worksheet, so different templates apply.
  • The evaluation of the rules is not necessarily in the given order, since all the normal mechanics of the rule engine still apply.

Chapter 24. Pet Store Example

24.1. Pet Store Example

All of the Java code for the Pet Store Example is contained in the file PetStore.java. It defines the following principal classes (in addition to several classes to handle Swing Events):
  • Petstore contains the main() method.
  • PetStoreUI is responsible for creating and displaying the Swing based GUI. It contains several smaller classes, mainly for responding to various GUI events such as mouse button clicks.
  • TableModel holds the table data. It is a JavaBean that extends the Swing class AbstractTableModel.
  • CheckoutCallback allows the GUI to interact with the Rules.
  • Ordershow keeps the items that the customer wishes to buy.
  • Purchase stores details of the order and the products the customer is buying.
  • Product is a JavaBean holding details of the product available for purchase and its price.

24.2. Pet Store Example: Creating the PetStore RuleBase in PetStore.main

KnowledgeBuilder kbuilder = KnowledgeBuilderFactory.newKnowledgeBuilder();

kbuilder.add( ResourceFactory.newClassPathResource( "PetStore.drl",
                                                    PetStore.class ),
              ResourceType.DRL );
KnowledgeBase kbase = KnowledgeBaseFactory.newKnowledgeBase();
kbase.addKnowledgePackages( kbuilder.getKnowledgePackages() );

// Create the stock.
Vector<Product> stock = new Vector<Product>();
stock.add( new Product( "Gold Fish", 5 ) );
stock.add( new Product( "Fish Tank", 25 ) );
stock.add( new Product( "Fish Food", 2 ) );

// A callback is responsible for populating the
// Working Memory and for firing all rules.
PetStoreUI ui = new PetStoreUI( stock,
                                new CheckoutCallback( kbase ) );
  • The code shown above loads the rules from a DRL file on the classpath. It does so via the second last line where a PetStoreUI object is created using a constructor. This accepts the Vector object stock that collects the products.
  • The CheckoutCallback class contains the Rule Base that has been loaded.

24.3. Pet Store Example: Firing Rules from CheckoutCallBack.checkout()

public String checkout(JFrame frame, List<Product> items) {
    Order order = new Order();

    // Iterate through list and add to cart
    for ( Product p: items ) {
        order.addItem( new Purchase( order, p ) );

    // Add the JFrame to the ApplicationData to allow for user interaction

    StatefulKnowledgeSession ksession = kbase.newStatefulKnowledgeSession();
    ksession.setGlobal( "frame", frame );
    ksession.setGlobal( "textArea", this.output );

    ksession.insert( new Product( "Gold Fish", 5 ) );
    ksession.insert( new Product( "Fish Tank", 25 ) );
    ksession.insert( new Product( "Fish Food", 2 ) );

    ksession.insert( new Product( "Fish Food Sample", 0 ) );

    ksession.insert( order );

    // Return the state of the cart
    return order.toString();
  • The Java code that fires the rules is within the CheckoutCallBack.checkout() method. This is triggered (eventually) when the Checkout button is pressed by the user.
  • Two items get passed into this method. One is the handle to the JFrame Swing component surrounding the output text frame, at the bottom of the GUI. The second is a list of order items. This comes from the TableModel storing the information from the "Table" area at the top right section of the GUI.
  • The for loop transforms the list of order items coming from the GUI into the Order JavaBean, also contained in the file PetStore.java.
  • All states in this example are stored in the Swing components. The rules are effectively stateless.
  • Each time the "Checkout" button is pressed, the code copies the contents of the Swing TableModel into the Session's Working Memory.
  • There are nine calls to the Working Memory. The first creates a new Working Memory as a Stateful Knowledge Session from the Knowledge Base. The next two pass in two objects that will be held as global variables in the rules. The Swing text area and the Swing frame used for writing messages.
  • More inserts put information on products into the Working Memory and the order list. The final call is the standard fireAllRules().

24.4. Pet Store Example: Package, Imports, Globals and Dialect from PetStore.drl

package org.drools.examples

import org.drools.WorkingMemory
import org.drools.examples.petstore.PetStoreExample.Order
import org.drools.examples.petstore.PetStoreExample.Purchase
import org.drools.examples.petstore.PetStoreExample.Product
import java.util.ArrayList
import javax.swing.JOptionPane;

import javax.swing.JFrame 
global JFrame frame 
global javax.swing.JTextArea textArea
  • The first part of file PetStore.drl contains the standard package and import statements to make various Java classes available to the rules.
  • The two globals frame and textArea hold references to the Swing components JFrame and JTextArea components that were previously passed on by the Java code calling the setGlobal() method. These global variables retain their value for the lifetime of the Session.

24.5. Pet Store Example: Java Functions in the Rules Extracted from PetStore.drl

function void doCheckout(JFrame frame, WorkingMemory workingMemory) {
    Object[] options = {"Yes",
    int n = JOptionPane.showOptionDialog(frame,
        "Would you like to checkout?",

    if (n == 0) {
        workingMemory.setFocus( "checkout" );

function boolean requireTank(JFrame frame, WorkingMemory workingMemory, Order order, Product fishTank, int total) {
    Object[] options = {"Yes",
    int n = JOptionPane.showOptionDialog(frame,
        "Would you like to buy a tank for your " + total + " fish?",
        "Purchase Suggestion",
    System.out.print( "SUGGESTION: Would you like to buy a tank for your "
                      + total + " fish? - " );

    if (n == 0) {
        Purchase purchase = new Purchase( order, fishTank );
        workingMemory.insert( purchase );
        order.addItem( purchase );
        System.out.println( "Yes" );
    } else {
        System.out.println( "No" );
    return true;
  • Having these functions in the rules file makes the Pet Store example more compact.
  • You can have the functions in a file of their own, within the same rules package, or as a static method on a standard Java class, and import them using import function my.package.Foo.hello.
  • doCheckout() displays a dialog asking users whether they wish to checkout. If they do, focus is set to the checkOut agenda-group, allowing rules in that group to (potentially) fire.
  • requireTank() displays a dialog asking users whether they wish to buy a tank. If so, a new fish tank Product is added to the order list in Working Memory.

24.6. Pet Store Example: Putting Items Into Working Memory from PetStore.drl

// Insert each item in the shopping cart into the Working Memory 
rule "Explode Cart"
    agenda-group "init"
    auto-focus true
    salience 10
    dialect "java"
    $order : Order( grossTotal == -1 )
    $item : Purchase() from $order.items
    insert( $item );
    kcontext.getKnowledgeRuntime().getAgenda().getAgendaGroup( "show items" ).setFocus();
    kcontext.getKnowledgeRuntime().getAgenda().getAgendaGroup( "evaluate" ).setFocus();
  • The first extract fires first because it has the auto-focus attribute set to true.
  • This rule matches against all orders that do not yet have their grossTotal calculated . It loops for each purchase item in that order. Some parts of the "Explode Cart" rule should be familiar: the rule name, the salience (suggesting the order for the rules being fired) and the dialect set to java.
  • agenda-group init defines the name of the agenda group. In this case, there is only one rule in the group. However, neither the Java code nor a rule consequence sets the focus to this group, and therefore it relies on the next attribute for its chance to fire.
  • auto-focus true ensures that this rule, while being the only rule in the agenda group, can fire when fireAllRules() is called from the Java code.
  • kcontext....setFocus() sets the focus to the show items and evaluate agenda groups in turn, permitting their rules to fire. In practice, you can loop through all items on the order, inserting them into memory, then firing the other rules after each insert.

24.7. Pet Store Example: Show Items in the GUI from PetStore.drl

rule "Show Items"
    agenda-group "show items"
    dialect "mvel"
    $order : Order( )
    $p : Purchase( order == $order )
   textArea.append( $p.product + "\n");
  • The show items agenda-group has only one rule, called "Show Items" (note the difference in case). For each purchase on the order currently in the Working Memory (or Session), it logs details to the text area at the bottom of the GUI. The textArea variable used for this is a global variables.
  • The evaluate Agenda group also gains focus from the Explode Cart rule.

24.8. Pet Store Example: Evaluate Agenda Group from PetStore.drl

// Free Fish Food sample when we buy a Gold Fish if we haven't already bought 
// Fish Food and don't already have a Fish Food Sample
rule "Free Fish Food Sample"
    agenda-group "evaluate"
    dialect "mvel"
    $order : Order()
    not ( $p : Product( name == "Fish Food") && Purchase( product == $p ) )
    not ( $p : Product( name == "Fish Food Sample") && Purchase( product == $p ) )
    exists ( $p : Product( name == "Gold Fish") && Purchase( product == $p ) )
    $fishFoodSample : Product( name == "Fish Food Sample" );
    System.out.println( "Adding free Fish Food Sample to cart" );
    purchase = new Purchase($order, $fishFoodSample);
    insert( purchase );
    $order.addItem( purchase ); 

// Suggest a tank if we have bought more than 5 gold fish and don't already have one
rule "Suggest Tank"
    agenda-group "evaluate"
    dialect "java"
    $order : Order()
    not ( $p : Product( name == "Fish Tank") && Purchase( product == $p ) )
    ArrayList( $total : size > 5 ) from collect( Purchase( product.name == "Gold Fish" ) )
    $fishTank : Product( name == "Fish Tank" )
    requireTank(frame, drools.getWorkingMemory(), $order, $fishTank, $total); 
The rule "Free Fish Food Sample" will only fire if:
  • The store does not already have any fish food, and
  • The store does not already have a free fish food sample, and
  • The store does have a Gold Fish in its order.
The rule "Suggest Tank" will only fire if
  • The store does notalready have a Fish Tank in its order, and
  • The store does have more than five Gold Fish Products in its order.
  • If the rule does fire, it calls the requireTank() function . This shows a Dialog to the user, and adding a Tank to the order and Working Memory if confirmed.
  • When calling the requireTank() function the rule passes the global frame variable so that the function has a handle to the Swing GUI.
  • If the rule does fire, it creates a new product (Fish Food Sample), and adds it to the order in Working Memory.

24.9. Pet Store Example: Doing the Checkout Extract from PetStore.drl

rule "do checkout"
    dialect "java"
        doCheckout(frame, drools.getWorkingMemory());
  • The rule "do checkout" has no agenda group set and no auto-focus attribute. As such, it is deemed part of the default (MAIN) agenda group. This group gets focus by default when all the rules in agenda-groups that explicitly had focus set to them have run their course.
  • There is no LHS to the rule, so the RHS will always call the doCheckout() function.
  • When calling the doCheckout() function, the rule passes the global frame variable to give the function a handle to the Swing GUI.
  • The doCheckout() function shows a confirmation dialog to the user. If confirmed, the function sets the focus to the checkout agenda-group, allowing the next lot of rules to fire.

24.10. Pet Store Example: Checkout Rules from PetStore.drl

rule "Gross Total"
    agenda-group "checkout"
    dialect "mvel"
   $order : Order( grossTotal == -1)
   Number( total : doubleValue )
       from accumulate( Purchase( $price : product.price ), sum( $price ) )
    modify( $order ) { grossTotal = total };
    textArea.append( "\ngross total=" + total + "\n" );

rule "Apply 5% Discount"
    agenda-group "checkout"
dialect "mvel"
   $order : Order( grossTotal >= 10 && < 20 )
   $order.discountedTotal = $order.grossTotal * 0.95;
   textArea.append( "discountedTotal total=" + $order.discountedTotal + "\n" );

rule "Apply 10% Discount"
    agenda-group "checkout"
    dialect "mvel"
   $order : Order( grossTotal >= 20 )
   $order.discountedTotal = $order.grossTotal * 0.90;
   textArea.append( "discountedTotal total=" + $order.discountedTotal + "\n" );
There are three rules in the checkout agenda-group:
  • Gross Total accumulates the product prices into a total, puts it into Working Memory, and displays it via the Swing JTextArea using the textArea global variable.
  • If the gross total is between 10 and 20, Apply 5% Discount calculates the discounted total and adds it to the Working Memory and displays it in the text area.
  • If the gross total is not less than 20, Apply 10% Discount calculates the discounted total and adds it to the Working Memory and displays it in the text area.

24.11. Pet Store Example: Running PetStore.java

To use PetStore.java, the following conditions must be met:
  1. The main() method has run and loaded the Rule Base but not yet fired the rules. So far, this is the only code in connection with rules that has been run.
  2. A new PetStoreUI object has been created and given a handle to the Rule Base, for later use.
  3. Swing components are deployed and the console waits for user input.
  • The file PetStore.java contains a main() method, so that it can be run as a standard Java application, either from the command line or via the IDE. This assumes you have your classpath set correctly.
  • The first screen that appears is the Pet Store Demo. It has a list of available products, an empty list of selected products, checkout and reset buttons, and an empty system messages area.
Pressing the "Checkout" button fires the business rules:
  1. Method CheckOutCallBack.checkout() is called by the Swing class waiting for the click on the "Checkout" button. This inserts the data from the TableModel object and inserts it into the Session's Working Memory. It then fires the rules.
  2. The first rule to fire will be the one with auto-focus set to true. It loops through all the products in the cart, ensures that the products are in the Working Memory, and then gives the Show Items and Evaluation agenda groups a chance to fire. The rules in these groups add the contents of the cart to the text area (at the bottom of the window), decide whether or not to give the user free fish food, and to ask us whether they want to buy a fish tank.

24.12. Pet Store Example: The Do Checkout Rule

  1. The Do Checkout rule is part of the default (MAIN) agenda group. It always calls the doCheckout() functionwhich displays a 'Would you like to Checkout?' dialog box.
  2. The doCheckout() function sets the focus to the checkout agenda-group, giving the rules in that group the option to fire.
  3. The rules in the checkout agenda-group display the contents of the cart and apply the appropriate discount.
  4. Swing then waits for user input to either checkout more products (and to cause the rules to fire again), or to close the GUI.

Chapter 25. Sudoku Example

25.1. Sudoku Example: Loading the Example

Procedure 25.1. Task

  1. Open sudoku.drl in the IDE.
  2. Execute java org.drools.examples.DroolsExamplesApp and click on SudokuExample. The window contains an empty grid, but the program comes with a number of grids stored internally which can be loaded and solved.
  3. Click on FileSamplesSimple to load one of the examples. All buttons are disabled until a grid is loaded. Loading the Simple example fills the grid according to the puzzle's initial state.
  4. Click on the Solve button and the JBoss Rules engine will fill out the remaining values. The buttons will be inactive again.
  5. Alternatively, click on the Step button to see the next digit found by the rule set. The Console window will display detailed information about the rules which are executing to solve the step in a readable format like the example below:
    single 8 at [0,1]
    column elimination due to [1,2]: remove 9 from [4,2]
    hidden single 9 at [1,2]
    row elimination due to [2,8]: remove 7 from [2,4]
    remove 6 from [3,8] due to naked pair at [3,2] and [3,7]
    hidden pair in row at [4,6] and [4,4]
  6. Click on the Dump button to see the state of the grid. The cells show either the established value or the remaining possible candidates. See the example below:
    Col: 0     Col: 1     Col: 2     Col: 3     Col: 4     Col: 5     Col: 6     Col: 7     Col: 8     
    Row 0:   2 4  7 9   2 456        4567 9   23 56  9  --- 5 ---  --- 1 ---    3  67 9  --- 8 ---     4 67   
    Row 1:  12    7 9  --- 8 ---  1    67 9   23  6  9  --- 4 ---   23  67    1 3  67 9    3  67 9  --- 5 --- 
    Row 2:  1  4  7 9  1  456     --- 3 ---      56 89      5 78       5678   --- 2 ---     4 67 9  1  4 67   
    Row 3:  1234       12345      1  45      12  5  8   --- 6 ---   2  5 78       5 78      45 7    --- 9 --- 
    Row 4:  --- 6 ---  --- 7 ---      5      --- 4 ---   2  5  8   --- 9 ---      5  8   --- 1 ---  --- 3 --- 
    Row 5:  --- 8 ---  12 45      1  45   9  12  5      --- 3 ---   2  5 7        567       4567     2 4 67   
    Row 6:  1 3   7    1 3  6     --- 2 ---    3 56 8       5  8     3 56 8   --- 4 ---    3 567 9  1    678  
    Row 7:  --- 5 ---  1 34 6     1  4 678     3  6 8   --- 9 ---    34 6 8   1 3  678   --- 2 ---  1    678  
    Row 8:    34       --- 9 ---     4 6 8   --- 7 ---  --- 1 ---   23456 8     3 56 8     3 56          6 8

25.2. Sudoku Example: Debugging a Broken Example

Procedure 25.2. Task

  1. Open sudoku.drl in your IDE.
  2. Click on FileSamples!DELIBERATLEY BROKEN!. The JBoss Rules engine will inspect the grid and produce the following output:
    cell [0,8]: 5 has a duplicate in row 0
    cell [0,0]: 5 has a duplicate in row 0
    cell [6,0]: 8 has a duplicate in col 0
    cell [4,0]: 8 has a duplicate in col 0
    Validation complete.
  3. Click on the Solve button to apply the solving rules to this invalid grid. These rules use the values of the cells for problem solving. The rules detecting these situations insert a Setting fact including the solution value for the specified cell. This fact removes the incorrect value from all cells in the group.

25.3. Sudoku Example: Java Source and Rules

  • The Java source code can be found in the /src/main/java/org/drools/examples/sudoku directory, with the two DRL files defining the rules located in the /src/main/rules/org/drools/examples/sudoku directory.
  • The package org.drools.examples.sudoku.swing contains a set of classes which implement a framework for Sudoku puzzles. This package does not have any dependencies on the JBoss Rules libraries.
  • SudokuGridModel defines an interface which can be implemented to store a Sudoku puzzle as a 9x9 grid of Cell objects.
  • SudokuGridView is a Swing component which can visualize any implementation of SudokuGridModel.
  • SudokuGridEvent and SudokuGridListener are used to communicate state changes between the model and the view. Events are fired when a cell's value is resolved or changed.
  • SudokuGridSamples provides a number of partially filled Sudoku puzzles for demonstration purposes.
  • The package org.drools.examples.sudoku.rules contains a utility class with a method for compiling DRL files.
  • The package org.drools.examples.sudoku contains a set of classes implementing the elementary Cell object and its various aggregations. It contains the CellFile subtypes CellRow, CellCol and CellSqr, all of which are subtypes of CellGroup.

25.4. Sudoku Example: Cell Objects

  • Cell and CellGroup are subclasses of SetOfNine, which provides a property free with the type Set<Integer>. For a Cell it represents the individual candidate set. For a CellGroup the set is the union of all candidate sets of its cells, or the set of digits that still need to be allocated.
  • You can write rules that detect the specific situations that permit the allocation of a value to a cell or the elimination of a value from some candidate set. For example, you can create a list of Cell objects with 81 Cell and 27 CellGroup objects. You can also combine the linkage provided by the Cell properties cellRow, cellCol, cellSqr and the CellGroup property cells.

25.5. Sudoku Example: Classes and Objects

  • An object belonging to the Setting class is used for triggering the operations that accompany the allocation of a value. The presence of a Setting fact is used in all rules that should detect changes in the process. This is to avoid reactions to inconsistent intermediary states.
  • An object of class Stepping is used in a low priority rule to execute an emergency halt when a "Step" ends unexpectedly. This indicates that the puzzle cannot be solved by the program.
  • The class org.drools.examples.sudoku.SudokuExample implements a Java application combining the above components.

25.6. Sudoku Example: Validate.drl

  • Sudoku Validator Rules (validate.drl) detect duplicate numbers in cell groups. They are combined in an agenda group which enables them to be activated after loading a puzzle.
  • The three rules duplicate in cell... are very similar. The first pattern locates a cell with an allocated value. The second pattern pulls in any of the three cell groups the cell belongs to. The final pattern finds a cell with the same value as the first cell and in the same row, column or square, respectively.
  • Rule terminate group fires last. It prints a message and calls halt.

25.7. Sudoku Example: Sudoku.drl

  • There are three types of solving rules in Sudoku.drl: one group handles the allocation of a number to a cell, another group detects feasible allocations, and the third group eliminates values from candidate sets.
  • The rules set a value, eliminate a value from Cell and retract setting depend on the presence of a Setting object.
  • Set a value handles the assignment to the cell and the operations for removing the value from the "free" sets of the cell's three groups. Also, it decrements a counter that, when zero, returns control to the Java application that has called fireUntilHalt().
  • Eliminate a value from Cell reduces the candidate lists of all cells that are related to the newly assigned cell.
  • Retract setting retracts the triggering Setting fact when all of the eliminations have been made.
  • There are just two rules that detect a situation where an allocation of a number to a cell is possible. Rule single fires for a Cell with a candidate set containing a single number. Rule hidden single fires when there is a cell containing a candidate but this candidate is absent from all other cells in one of the groups the cell belongs to. Both rules create and insert a Setting fact.
  • Rules from the largest group of rules implement, singly or in groups of two or three, various solving techniques, as they are employed when solving Sudoku puzzles manually.
  • Rule naked pair detects two identical candidate sets in two cells of a group. These two values may be removed from all other candidate sets of that group.
  • In hidden pair in rules, the rules look for a subset of two numbers in exactly two cells of a group, with neither value occurring in any of the other cells of this group. This means that all other candidates can be eliminated from the two cells harbouring the hidden pair.
  • A pair of rules deals with X-wings in rows and columns. When there are only two possible cells for a value in each of two different rows (or columns) and these candidates are in the same columns (or rows), then all other candidates for this value in the columns (or rows) can be eliminated. The conditions same or only result in patterns with suitable constraints or prefixed with not.
  • The rule pair intersection removal... is based on the restricted occurrence of a number within one square, either in a single row or in a single column. This means that this number must be in one of those two or three cells of the row or column. It can be removed from the candidate sets of all other cells of the group. The pattern establishes the restricted occurrence and then fires for each cell outside the square and within the same cell file.
  • To solve very difficult grids, the rule set would need to be extended with more complex rules. (Ultimately, there are puzzles that cannot be solved except by trial and error.)

Chapter 26. Number Guess Example

26.1. Number Guess Example: Loading the Example

final KnowledgeBuilder kbuilder = KnowledgeBuilderFactory.newKnowledgeBuilder();
kbuilder.add( ResourceFactory.newClassPathResource( "NumberGuess.drl",
                                                    ShoppingExample.class ),
              ResourceType.DRL );
kbuilder.add( ResourceFactory.newClassPathResource( "NumberGuess.rf",
                                                    ShoppingExample.class ),
              ResourceType.DRF );

final KnowledgeBase kbase = KnowledgeBaseFactory.newKnowledgeBase();
kbase.addKnowledgePackages( kbuilder.getKnowledgePackages() );
  • The Number Guess example located in NumberGuess.drl shows the use of Rule Flow, a way of controlling the order in which rules are fired. It is loaded as shown above.

26.2. Number Guess Example: Starting the RuleFlow

final StatefulKnowledgeSession ksession = kbase.newStatefulKnowledgeSession();

KnowledgeRuntimeLogger logger =
  KnowledgeRuntimeLoggerFactory.newFileLogger(ksession, "log/numberguess");

ksession.insert( new GameRules( 100, 5 ) );
ksession.insert( new RandomNumber() );
ksession.insert( new Game() );

ksession.startProcess( "Number Guess" );


  • The above code demonstrates the creation of the package and the loading of the rules (using the add() method).
  • There is an additional line to add the Rule Flow (NumberGuess.rf), which provides the option of specifying different rule flows for the same Knowledge Base.
  • Once the Knowledge Base is created it can be used to obtain a Stateful Session. The facts are then inserted.

26.3. Number Guess Example: Classes and Methods


The Number Guess Example classes are all contained within the NumberGuessExample.java file.
  • Class GameRules provides the maximum range and the number of guesses allowed.
  • Class RandomNumber automatically generates a number between 0 and 100 and makes it available to the rules. It does so by insertion via the getValue() method.
  • Class Game keeps track of the number of guesses made.
  • To start the process, the startProcess() method is called.
  • To execute the rules, the fireAllRules() method is called.
  • To clear the Working Memory session, the dispose() method is called.

26.4. Number Guess Example: Observing the RuleFlow

Procedure 26.1. Task

  1. Open the NumberGuess.rf file in the Drools IDE. A diagram will appear that works much like a standard flowchart.
  2. To edit the diagram, use the menu of available components to the left of the diagram in the IDE. This is called a palette.
  3. Save the diagram in XML. (If installed, you can utilise XStream to do this.)
  4. If it is not already open, ensure that the Properties View is visible in the IDE. It can be opened by clicking WindowShow ViewOther where you can select the Properties view. If you do this before you select an item on the rule flow (or click on the blank space in the rule flow) you will see the properties. You can use these properties to identify processes and observe changes.

26.5. Number Guess Example: RuleFlow Nodes

In the Number Guess RuleFlow there are several node types:
  • The Start node (white arrow in a green circle) and the End node (red box) mark beginning and end of the rule flow.
  • A Rule Flow Group box (yellow, without an icon) represents a Rule Flow Groups defined in the rules (DRL) file. For example, when the flow reaches the Rule Flow Group "Too High", only those rules marked with an attribute of ruleflow-group "Too High" can potentially fire.
  • Action nodes (yellow cog-shaped icon) perform standard Java method calls. Most action nodes in this example call System.out.println(), indicating the program's progress to the user.
  • Split and Join Nodes (blue ovals, no icon) such as "Guess Correct?" and "More guesses Join" mark places where the flow of control can split and rejoin.
  • Arrows indicate the flow between the various nodes.

26.6. Number Guess Example: Firing Rules at a Specific Point in NumberGuess.drl

rule "Get user Guess"
    ruleflow-group "Guess"
        $r : RandomNumber()
        rules : GameRules( allowed : allowedGuesses )
        game : Game( guessCount < allowed )
        not ( Guess() )
        System.out.println( "You have " + ( rules.allowedGuesses - game.guessCount )
                            + " out of " + rules.allowedGuesses
                            + " guesses left.\nPlease enter your guess from 0 to "
                            + rules.maxRange );
        br = new BufferedReader( new InputStreamReader( System.in ) );
        i = br.readLine();        
        modify ( game ) { guessCount = game.guessCount + 1 }
        insert( new Guess( i ) );
  • The various nodes in combination with the rules make the Number Guess game work. For example, the "Guess" Rule Flow Group allows only the rule "Get user Guess" to fire, because only that rule has a matching attribute of ruleflow-group "Guess".
  • The LHS section (after when) of the rule states that it will be activated for each RandomNumber object inserted into the Working Memory where guessCount is less than allowedGuesses from the GameRules object and where the user has not guessed the correct number.
  • The RHS section (or consequence, after then) prints a message to the user and then awaits user input from System.in. After obtaining this input (the readLine() method call blocks until the return key is pressed) it modifies the guess count and inserts the new guess, making both available to the Working Memory.
  • The package declares the dialect as MVEL and various Java classes are imported.
In total, there are five rules in this file:
  1. Get User Guess, the Rule examined above.
  2. A Rule to record the highest guess.
  3. A Rule to record the lowest guess.
  4. A Rule to inspect the guess and retract it from memory if incorrect.
  5. A Rule that notifies the user that all guesses have been used up.

26.7. Number Guess Example: Viewing RuleFlow Constraints

Procedure 26.2. Task

  1. In the IDE, go to the Properties view and open the Constraints Editor by clicking on the "Constraints" property line.
  2. Click on the Edit button beside To node Too High to open the dialogue which will present you with various options. The values in the Textual Editor window follow the standard rule format for the LHS and can refer to objects in Working Memory. The consequence (RHS) is that the flow of control follows this node (that is, To node Too High) if the LHS expression evaluates to true.

26.8. Number Guess Example: Console Output

You have 5 out of 5 guesses left.
Please enter your guess from 0 to 100
Your guess was too high
You have 4 out of 5 guesses left.
Please enter your guess from 0 to 100
Your guess was too low
You have 3 out of 5 guesses left.
Please enter your guess from 0 to 100
Your guess was too low
You have 2 out of 5 guesses left.
Please enter your guess from 0 to 100
Your guess was too low
You have 1 out of 5 guesses left.
Please enter your guess from 0 to 100
Your guess was too low
You have no more guesses
The correct guess was 48 

  • Since the file NumberGuess.java contains a main() method, it can be run as a standard Java application, either from the command line or via the IDE. A typical game might result in the interaction above. The numbers in bold were typed in by the user.
  • The main() method of NumberGuessExample.java loads a Rule Base, creates a Stateful Session and inserts Game, GameRules and RandomNumber (containing the target number) objects into it. The method also sets the process flow to be used and fires all rules. Control passes to the RuleFlow.
  • The RuleFlow file NumberGuess.rf begins at the "Start" node.
  • At the Guess node, the appropriate Rule Flow Group ("Get user Guess") is enabled. In this case the Rule "Guess" (in the NumberGuess.drl file) is triggered. This rule displays a message to the user, takes the response, and puts it into Working Memory. Flow passes to the next Rule Flow Node.
  • At the next node, "Guess Correct", constraints inspect the current session and decide which path to take.
    If the guess in step 4 was too high or too low, flow proceeds along a path which has an action node with normal Java code printing a suitable message and a Rule Flow Group causing a highest guess or lowest guess rule to be triggered. Flow passes from these nodes to step 6.
    If the guess in step 4 was right, we proceed along the path towards the end of the RuleFlow. Before this, an action node with normal Java code prints a statement "you guessed correctly". There is a join node here (just before the Rule Flow end) so the no-more-guesses path (step 7) can also terminate the RuleFlow.
  • Control passes as per the RuleFlow via a join node to a "guess incorrect" RuleFlow Group (triggering a rule to retract a guess from Working Memory) and onto the "More guesses" decision node.
  • The "More guesses" decision node (on the right hand side of the rule flow) uses constraints, again looking at values that the rules have put into the working memory, to decide if the user has more guesses and. If so, it moves to step 3. If not, the user proceeds to the end of the RuleFlow via a RuleFlow Group that triggers a rule stating "you have no more guesses".
  • The loop over steps 3 to 7 continues until the number is guessed correctly or the user runs out of guesses.

Appendix A. Revision History

Revision History
Revision 5.3.1-33.4002013-10-31Rüdiger Landmann
Rebuild with publican 4.0.0
Revision 5.3.1-33Tue Aug 20 2013 Red Hat Content Services
Improvements have been made to the structure of the guide.

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