Impact of mutation operators on the ratio of equivalent mutants

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

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

Abstract

Software mutation is a widely used technique of software testing that consists in generating variants of a base program by applying standard modifications to its source code. One of the main obstacles in the use of software mutations is the existence of equivalent mutants, i.e. mutants whose behavior is indistinguishable from the base program, even though their source code is distinct. Despite several decades of research, the identification of equivalent mutants remains an open problem. Rather than attempting to identify individual mutants that are equivalent to the base, we argue that it is often sufficient to estimate the number of equivalent mutants; also, we argue that the number of equivalent mutants depends on two factors that must be considered in the estimation effort, namely the base program and the mutation operators that are used; in this paper, we explore the impact of mutation operators on the number of equivalent mutants.

Original languageEnglish (US)
Title of host publicationNew Trends in Intelligent Software Methodologies, Tools and Techniques - Proceedings of the 17th International Conference, SoMeT 2018
EditorsHamido Fujita, Enrique Herrera-Viedma
PublisherIOS Press BV
Pages664-677
Number of pages14
ISBN (Electronic)9781614998990
DOIs
StatePublished - 2018
Event17th International Conference on New Trends in Intelligent Software Methodology Tools and Techniques, SoMeT 2018 - Granada, Spain
Duration: Sep 26 2018Sep 28 2018

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume303
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314

Conference

Conference17th International Conference on New Trends in Intelligent Software Methodology Tools and Techniques, SoMeT 2018
Country/TerritorySpain
CityGranada
Period9/26/189/28/18

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

Keywords

  • Equivalent mutants
  • Mutation operators
  • Semantic metrics
  • Software mutation
  • Software testing

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