Quantifying the Effectiveness of Mutant Sets

Samia Alblwi, Amani Ayad, Besma Khaireddine, Imen Marsit, Ali Mili

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

Abstract

To reduce the cost of mutation testing, researchers have sought to find minimal mutant sets. As an optimization problem, mutant set minimization is defined by two parameters: the objective function that we must optimize; and the constraint under which the optimization is carried out. Whereas the objective function of this optimization problem is clear (minimizing the cardinality of the mutant set), the constraint under which this optimization is attempted has not been clearly articulated in the literature. In this paper, we propose a formal definition of this constraint and discuss in what sense, and to what extent, published algorithms of mutant set minimization comply with this constraint.

Original languageEnglish (US)
Title of host publicationProceedings - 2022 IEEE 22nd International Conference on Software Quality, Reliability and Security Companion, QRS-C 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages288-297
Number of pages10
ISBN (Electronic)9798350319910
DOIs
StatePublished - 2022
Event22nd IEEE International Conference on Software Quality, Reliability and Security Companion, QRS-C 2022 - Virtual, Online, China
Duration: Dec 5 2022Dec 9 2022

Publication series

NameProceedings - 2022 IEEE 22nd International Conference on Software Quality, Reliability and Security Companion, QRS-C 2022

Conference

Conference22nd IEEE International Conference on Software Quality, Reliability and Security Companion, QRS-C 2022
Country/TerritoryChina
CityVirtual, Online
Period12/5/2212/9/22

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Modeling and Simulation

Keywords

  • Mutant set effectiveness
  • Mutant set minimization
  • Mutant subsumption
  • Mutation testing

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