DaMAT: A Data-driven Mutation Analysis Tool

Enrico Vigano, Oscar Cornejo, Fabrizio Pastore, Lionel Briand

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We present DaMAT, a tool that implements data-driven mutation analysis. In contrast to traditional code-driven mutation analysis tools it mutates (i.e., modifies) the data ex-changed by components instead of the source of the software under test. Such an approach helps ensure that test suites appropriately exercise components interoperability - essential for safety-critical cyber-physical systems. A user-provided fault model drives the mutation process. We have successfully evalu-ated DaMAT on software controlling a microsatellite and a set of libraries used in deployed CubeSats. A demo video of DaMAT is available at https://youtu.be/sSMS2xWCj84

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE/ACM 45th International Conference on Software Engineering
Subtitle of host publicationCompanion, ICSE-Companion 2023
PublisherIEEE Computer Society
Pages165-169
Number of pages5
ISBN (Electronic)9798350322637
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event45th IEEE/ACM International Conference on Software Engineering: Companion, ICSE-Companion 2023 - Melbourne, Australia
Duration: 14 May 202320 May 2023

Publication series

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

Conference

Conference45th IEEE/ACM International Conference on Software Engineering: Companion, ICSE-Companion 2023
Country/TerritoryAustralia
CityMelbourne
Period14/05/2320/05/23

Keywords

  • CPS
  • Mutation analysis

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