Topsy-Turvy: A smarter and faster parallelization of mutation analysis

Rahul Gopinath, Carlos Jensen, Alex Groce

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Scopus citations


Mutation analysis is an effective, if computationally expensive, technique that allows practitioners to accurately evaluate the quality of their test suites. To reduce the time and cost of mutation analysis, researchers have looked at parallelizing mutation runs - - running multiple mutated versions of the program in parallel, and running through the tests in sequence on each mutated program until a bug is found. While an improvement over sequential execution of mutants and tests, this technique carries a significant overhead cost due to its redundant execution of unchanged code paths. In this paper we propose a novel technique (and its implementation) which parallelizes the test runs rather than the mutants, forking mutants from a single program execution at the point of invocation, which reduces redundancy. We show that our technique can lead to significant efficiency improvements and cost reductions.

Original languageEnglish (US)
Title of host publicationProceedings - 5th International Workshop on Green and Sustainable Software, GREENS 2016
PublisherIEEE Computer Society
Number of pages4
ISBN (Electronic)9781450341615, 9781450342056
StatePublished - May 14 2016
Externally publishedYes
Event2016 IEEE/ACM 38th IEEE International Conference on Software Engineering, ICSE 2016 - Austin, United States
Duration: May 14 2016May 22 2016

Publication series

NameProceedings - International Conference on Software Engineering
ISSN (Print)0270-5257


Conference2016 IEEE/ACM 38th IEEE International Conference on Software Engineering, ICSE 2016
Country/TerritoryUnited States


  • Mutation analysis
  • Parallelization
  • Software testing

ASJC Scopus subject areas

  • Software


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