A Variability Perspective of Mutation Analysis

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Résumé

Mutation testing is an effective technique for either improving or generating fault-finding test suites. It creates defective or incorrect program artifacts of the program under test and evaluates the ability of test suites to reveal them. Despite being effective, mutation is costly since it requires assessing the test cases with a large number of defective artifacts. Even worse, some of these artifacts are behaviourally "equivalent" to the original one and hence, they unnecessarily increase the testing effort. We adopt a variability perspective on mutation analysis. We model a defective artifact as a transition system with a specific feature selected and consider it as a member of a mutant family. The mutant family is encoded as a Featured Transition System, a compact formalism initially dedicated to model-checking of software product lines. We show how to evaluate a test suite against the set of all candidate defects by using mutant families. We can evaluate all the considered defects at the same time and isolate some equivalent mutants. We can also assist the test generation process and eciently consider higher-order mutants.
langue originaleAnglais
titreProceedings of the 22Nd ACM SIGSOFT International Symposium on Foundations of Software Engineering
Lieu de publicationNew York, NY, USA
EditeurACM Press
Pages841-844
Nombre de pages4
Les DOIs
étatPublié - 16 nov. 2014
Evénement22nd ACM SIGSOFT International Symposium on the Foundations of Software Engineering (FSE '14) - , Hong-Kong
Durée: 16 nov. 201421 nov. 2014

Série de publications

NomFSE 2014
EditeurACM

Une conférence

Une conférence22nd ACM SIGSOFT International Symposium on the Foundations of Software Engineering (FSE '14)
PaysHong-Kong
période16/11/1421/11/14

    Empreinte digitale

Contient cette citation

Devroey, X., Perrouin, G., Cordy, M., Papadakis, M., Legay, A., & Schobbens, P-Y. (2014). A Variability Perspective of Mutation Analysis. Dans Proceedings of the 22Nd ACM SIGSOFT International Symposium on Foundations of Software Engineering (p. 841-844). (FSE 2014). New York, NY, USA: ACM Press. https://doi.org/10.1145/2635868.2666610