Using Semantic Metrics to Predict Mutation Equivalence

Amani Ayad, Imen Marsit, Nazih Mohamed Omri, Ji Meng Loh, Ali Mili

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

4 Scopus citations


Equivalent mutants are a major nuisance in mutation testing because they introduce a significant amount of bias. But weeding them out is difficult because it requires a detailed analysis of the source code of the base program and the mutant. In this paper we argue that for most applications, it is not necessary to identify equivalent mutants individually; rather it suffices to estimate their number. Also, we explore how we can estimate their number by a cursory/automatable analysis of the base program and the mutant generation policy.

Original languageEnglish (US)
Title of host publicationSoftware Technologies - 13th International Conference, ICSOFT 2018, Revised Selected Papers
EditorsLeszek A. Maciaszek, Leszek A. Maciaszek, Marten van Sinderen
PublisherSpringer Verlag
Number of pages25
ISBN (Print)9783030291563
StatePublished - 2019
Event13th International Conference on Software Technologies, ICSOFT 2018 - Porto, Portugal
Duration: Jul 26 2018Jul 28 2018

Publication series

NameCommunications in Computer and Information Science
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937


Conference13th International Conference on Software Technologies, ICSOFT 2018

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • General Mathematics


  • Mutant equivalence
  • Mutant survival ratio
  • Redundancy
  • Software metrics


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