I think I could use a slightly more detailed explanation of what it is and how it works at the high level. The website doesn't fully explain it.

e.g. The about page, as of this writing, does not say anything about the project.

https://otava.apache.org/docs/overview

Change Detection for Continuous Performance Engineering: Otava performs statistical analysis of performance test results stored in CSV files, PostgreSQL, BigQuery, or Graphite database. It finds change-points and notifies about possible performance regressions.

You can also read "8 Years of Optimizing Apache Otava: How disconnected open source developers took an algorithm from n3 to constant time" - https://arxiv.org/abs/2505.06758v1

and "The Use of Change Point Detection to Identify Software Performance Regressions in a Continuous Integration System" - https://arxiv.org/abs/2003.00584 (and I guess this blog post https://www.mongodb.com/company/blog/engineering/using-chang... )

(https://en.wikipedia.org/wiki/Change_detection explains what's change detection)

It's hilarious that the about page doesn't tell you anything about the project

I would be interested in a layperson summary of how this code deals with whacky distributions produced by computer systems. I am too stupid to understand anything more complex than introductory SPC which struggles with non-normal distributions.

Change Detection for tests. The algorithm: https://otava.apache.org/docs/math