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Title Tracking Down Performance Variation against Source Code Evolution
Authors Juan Pablo Sandoval Alcocer, Alexandre Bergel
Publication date 2015
Abstract Little is known about how software performance evolves
across
software revisions. The severity of this situation is high since (i) most
performance variations seem to happen accidentally and (ii) addressing a
performance regression is challenging, especially when functional code is
stacked on it. This paper reports an empirical study on the performance
evolution of 19 applications, totaling over 19 MLOC. It took 52 days to run
our 49 benchmarks. By relating performance variation with source code
revisions, we found out that: (i) 1 out of every 3 application revisions
introduces a performance variation, (ii) performance variations may be
classified into 9 patterns, (iii) the most prominent cause of performance
regression involves loops and collections. We carefully describe the
patterns we identified, and detail how we addressed the numerous challenges
we faced to complete our experiment.
Pages 129-139
Conference name Dynamic Languages Symposium
Publisher ACM Press (New York, NY, USA)
Reference URL View reference page