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dc.contributor.authorBetka, Maik-
dc.contributor.authorWagner, Stefan-
dc.date.accessioned2024-08-14T12:24:34Z-
dc.date.available2024-08-14T12:24:34Z-
dc.date.issued2022de
dc.identifier.issn2047-7481-
dc.identifier.issn2047-7473-
dc.identifier.other1898783780-
dc.identifier.urihttp://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-148361de
dc.identifier.urihttp://elib.uni-stuttgart.de/handle/11682/14836-
dc.identifier.urihttp://dx.doi.org/10.18419/opus-14817-
dc.description.abstractMutation testing is a technique that changes code instructions to assess the quality of automated software tests. Industry has not broadly adopted the technique because execution and analysis times are too long and not considered worth the effort. To change this, a variation called “extreme mutation testing” emerged, which mutates whole methods instead of instructions. The extreme variant trades accuracy for speed gains and also provides pre‐analyzed results. In this study, we aim to analyze both techniques on their granularity levels, look for benefits when combining them, and find motivations when a developer considers killing mutants. For that, we conducted a case study in a company from the semiconductor industry. We mutated a large Java software project which is tested by more than 11,000 unit tests, analyzed the results, manually inspected more than 1000 mutants, and conducted a focus group with five developers of the software. Among other results, we provide the distribution of traditional across extreme mutants as well as qualitative coding results of our mutant inspection and focus group transcript. We conclude that the traditional approach can be similarly strategically applied as the extreme one and that motivations of developers to target mutants are mostly not code related.en
dc.description.sponsorshipAdvantestde
dc.language.isoende
dc.relation.uridoi:10.1002/smr.2450de
dc.rightsinfo:eu-repo/semantics/openAccessde
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/de
dc.subject.ddc620de
dc.titleTowards practical application of mutation testing in industry : traditional versus extreme mutation testingen
dc.typearticlede
dc.date.updated2023-11-14T00:09:39Z-
ubs.fakultaetInformatik, Elektrotechnik und Informationstechnikde
ubs.institutInstitut für Software Engineeringde
ubs.publikation.seiten29de
ubs.publikation.sourceJournal of software : evolution and process 34 (2022), No. e2450de
ubs.publikation.typZeitschriftenartikelde
Enthalten in den Sammlungen:05 Fakultät Informatik, Elektrotechnik und Informationstechnik

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