[ https://issues.redhat.com/browse/JBTM-3137?page=com.atlassian.jira.plugin... ] Mayank Kunwar commented on JBTM-3137: ------------------------------------- For this issue I made two changes: 1. There is a article for making the benchmark more effective and using JMH in proper manner (best practices) so that we could get more accurate performance. Here is the article link https://www.researchgate.net/publication/333825812_What's_Wrong_With_... Under this article, the author has provided a plugin for finding JMH related bugs. So we have to import this plugin on top of Spotbug plugin in IDE. So, once I imported JMH spotbug plugin and applied it to the performance repo, it was reporting some bugs related to JMH usage. We were not using JMH effectively. So I fixed all these bugs, reported by the mentioned plugin. Under the article that I mentioned above, it says that we have to restrict JVM optimization by using Blackhole (from JMH), so that we could evaluate performance of the Tests more effectively. 2. I did an experiment with a simple program, in order to evaluate more appropriate JMH argument, which will provide us with more accurate performance results. Maybe these values can be tuned, further more effectively. I think tuning these values is a tricky part. Here is a simple program. @Benchmark public boolean evaluateJMHParam(Blackhole bh) { for(int i=0; i<10;i++){ bh.consume(Math.log(i)); } return true; } After iterating the JMH arguments, five times each, for different combinations of JMH arguments, got to a conclusion to use *JMH Arguments* as : -t $i -r 30 -f 3 -wi 5 -i 5 t - thread count r - measurement run time f - fork wi - warmup iterations i - iterations In the above JMH arguments: the $i that is thread count, that will vary. Values for $i will be [1, 24, 240, 1600] -- This message was sent by Atlassian Jira (v7.13.8#713008)