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Is mutation score a fair metric?

Published:20 October 2019Publication History

ABSTRACT

Comparing the mutation scores achieved for test suites, one is able to judge which test suite is more effective. However, it is not known if the mutation score is a fair metric to do such comparison. In this paper, we present an empirical study, which compares developer-written and automatically generated test suites in terms of mutation score and in relation to the detection ratios of 7 mutation types. Our results indicate fairness on the mutation score.

References

  1. 2019. EvoSuite: Automatic Test Suite Generation for Java (2019). http://www.evosuite.org/evosuite/ Accessed: 2019-09-04.Google ScholarGoogle Scholar
  2. 2019. PITest Mutation Testing Tool for Java (2019). http://pitest.org/ Accessed: 2019-09-04.Google ScholarGoogle Scholar
  3. 2019. Randoop: Automatic unit test generation for Java (2019). https://randoop.github.io/randoop/ Accessed: 2019-09-04.Google ScholarGoogle Scholar
  4. Michael Andersson. 2017. An Experimental Evaluation of PIT's Mutation Operators. Bachelor thesis. Umeå University.Google ScholarGoogle Scholar
  5. J. H. Andrews, L. C. Briand, and Y. Labiche. 2005. Is mutation an appropriate tool for testing experiments? [software testing]. In Proceedings. 27th International Conference on Software Engineering, 2005. ICSE 2005. IEEE, Saint Louis, MO, USA, USA, 402-411. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Henry Coles, Thomas Laurent, Christopher Henard, Mike Papadakis, and Anthony Ventresque. 2016. PIT: A Practical Mutation Testing Tool for Java (Demo). In Proceedings of the 25th International Symposium on Software Testing and Analysis (ISSTA 2016). ACM, New York, NY, USA, 449-452. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Leonardo Fernandes, Márcio Ribeiro, Luiz Carvalho, Rohit Gheyi, Melina Mongiovi, André Santos, Ana Cavalcanti, Fabiano Ferrari, and José Carlos Maldonado. 2017. Avoiding Useless Mutants. In Proceedings of the 16th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences (GPCE 2017). ACM, New York, NY, USA, 187-198. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Gordon Fraser and Andrea Arcuri. 2011. EvoSuite: Automatic Test Suite Generation for Object-oriented Software. In Proceedings of the 19th ACM SIGSOFT Symposium and the 13th European Conference on Foundations of Software Engineering (ESEC/FSE '11). ACM, New York, NY, USA, 416-419. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. James H. Andrews, Lionel Briand, Yvan Labiche, and Akbar Siami Namin. 2006. Using Mutation Analysis for Assessing and Comparing Testing Coverage Criteria. Software Engineering, IEEE Transactions on 32 (09 2006), 608-624. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Y. Jia and M. Harman. 2011. An Analysis and Survey of the Development of Mutation Testing. IEEE Transactions on Software Engineering 37, 5 (Sep. 2011), 649-678. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. René Just, Darioush Jalali, Laura Inozemtseva, Michael D. Ernst, Reid Holmes, and Gordon Fraser. 2014. Are Mutants a Valid Substitute for Real Faults in Software Testing?. In Proceedings of the 22Nd ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE 2014). ACM, New York, NY, USA, 654-665. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. M. Kintis, M. Papadakis, Y. Jia, N. Malevris, Y. Le Traon, and M. Harman. 2018. Detecting Trivial Mutant Equivalences via Compiler Optimisations. IEEE Transactions on Software Engineering 44, 4 (April 2018), 308-333.Google ScholarGoogle ScholarCross RefCross Ref
  13. J. S. Kracht, J. Z. Petrovic, and K. R. Walcott-Justice. 2014. Empirically Evaluating the Quality of Automatically Generated and Manually Written Test Suites. In 2014 14th International Conference on Quality Software. IEEE, Dallas, TX, USA, 256-265. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Carlos Pacheco and Michael D. Ernst. 2007. Randoop: Feedback-directed Random Testing for Java. In Companion to the 22Nd ACM SIGPLAN Conference on Object-oriented Programming Systems and Applications Companion (OOPSLA '07). ACM, New York, NY, USA, 815-816. Google ScholarGoogle ScholarDigital LibraryDigital Library

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      cover image ACM Conferences
      SPLASH Companion 2019: Proceedings Companion of the 2019 ACM SIGPLAN International Conference on Systems, Programming, Languages, and Applications: Software for Humanity
      October 2019
      58 pages
      ISBN:9781450369923
      DOI:10.1145/3359061

      Copyright © 2019 ACM

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      Publication History

      • Published: 20 October 2019

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