Sufficient mutation operators for measuring test effectiveness

Akbar Siami Namin, James H. Andrews, Duncan J. Murdoch

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

113 Scopus citations

Abstract

Mutants are automatically-generated, possibly faulty variants of programs. The mutation adequacy ratio of a test suite is the ratio of non-equivalent mutants it is able to identify to the total number of non-equivalent mutants. This ratio can be used as a measure of test effectiveness. However, it can be expensive to calculate, due to the large number of different mutation operators that have been proposed for generating the mutants. In this paper, we address the problem of finding a small set of mutation operators which is still sufficient for measuring test effectiveness. We do this by defining a statistical analysis procedure that allows us to identify such a set, together with an associated linear model that predicts mutation adequacy with high accuracy. We confirm the validity of our procedure through cross-validation and the application of other, alternative statistical analyses.

Original languageEnglish
Title of host publicationICSE'08
Subtitle of host publicationProceedings of the 30th International Conference on Software Engineering 2008
Pages351-360
Number of pages10
DOIs
StatePublished - 2008
Event30th International Conference on Software Engineering 2008, ICSE'08 - Leipzig, Germany
Duration: May 10 2008May 18 2008

Publication series

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

Conference

Conference30th International Conference on Software Engineering 2008, ICSE'08
CountryGermany
CityLeipzig
Period05/10/0805/18/08

Keywords

  • Mutation analysis
  • Testing effectiveness

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  • Cite this

    Namin, A. S., Andrews, J. H., & Murdoch, D. J. (2008). Sufficient mutation operators for measuring test effectiveness. In ICSE'08: Proceedings of the 30th International Conference on Software Engineering 2008 (pp. 351-360). (Proceedings - International Conference on Software Engineering). https://doi.org/10.1145/1368088.1368136