How to benchmark: the Measure-Explain-Test-Improve loop

Abstract

I would like to share recommendations on how to do performance benchmarks for the purpose of computer science research evaluation. Research in my field (programming language research) often involves performance considerations, but it is typically not the main tool used to evaluate our research (typically we evaluate via formal statements and their proofs, experience writing large or interesting examples, or systematic comparison of expressivity, feature set, etc.). My impression is that, as a result, we tend to not do our performance evaluation very well. In the present document I will try to explain a methodology to do benchmarking correctly (I hope!). People with no former benchmarking experience should be able to build solid performance evaluation as part of their research. I explain the justification for each aspect along the way.

0

Turn this paper into a full lesson

ArcXiv compiles a staged curriculum from this paper: 8-12 lessons across beginner → advanced, synthesised section guides, visuals, flashcards, a quiz, exercises, and on-demand deep dives per section. Grounded in the abstract, never invented.

Discussion (0)

Sign in to join the discussion.

Loading comments…