Chapter 6. Optimize Windup Performance

Windup performance depends on a number of factors, including hardware configuration, the number and types of files in the application, the size and number of applications to be evaluated, and whether the application contains source or compiled code. For example, a file that is larger than 10 MB may need a lot of time to process.

In general, Windup spends about 40% of the time decompiling classes, 40% of the time executing rules, and the remainder of the time processing other tasks and generating reports. This section describes what you can do to improve the performance of Windup.

6.1. Tips to Optimize Performance

6.1.1. Application and Command-Line Suggestions

Try these suggestions first before upgrading hardware.

  • If possible, execute Windup against the source code instead of the archives. This eliminates the need to decompile additional JARs and archives.
  • Specify a comma-separated list of the packages to be evaluated by Windup using the --packages argument on the WINDUP_HOME/bin/windup command line. If you omit this argument, Windup will decompile everything, which has a big impact on performance.
  • Specify the --excludePackages and --excludeTags arguments where possible to exclude them from processing.
  • Add additional proprietary packages that should not be processed to the ignore/proprietary.package-ignore.txt file in the Windup distribution directory. Windup can still find the references to the packages in the application source code, but avoids the need to decompile and analyze the proprietary classes.
  • If you have access to a server that has better resources than your laptop or desktop machine, you may want to consider running Windup on that server.

6.1.2. Hardware Upgrade Suggestions

If the application and command-line suggestions above do not improve performance, you may need to upgrade your hardware.

  • If you have access to a server that has better resources than your laptop/desktop, then you may want to consider running Windup on that server.
  • Very large applications that require decompilation have large memory requirements. 8 GB RAM is recommended. This allows 3 - 4 GB RAM for use by the JVM.
  • An upgrade from a single or dual-core to a 4-core CPU processor provides better performance.
  • Disk space and fragmentation can impact performance. A fast disk, especially a solid-state drive (SSD), with greater than 4 GB of defragmented disk space should improve performance.