RacerF: Data Race Detection with Frama-C (Competition Contribution)

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dc.contributor.authorDacík, Tomášcs
dc.contributor.authorVojnar, Tomášcs
dc.coverage.volume15698cs
dc.date.accessioned2025-10-21T07:05:37Z
dc.date.available2025-10-21T07:05:37Z
dc.date.issued2025-05-01cs
dc.description.abstractRacerF is a static analyser for detection of data races in multithreaded C programs implemented as a  plugin of the Frama-C platform. The approach behind RacerF is mostly heuristic and relies on analysis of the sequential behaviour of particular threads whose results are generalised using a combination of under- and over-approximating techniques to allow analysis of the multithreading behaviour. In particular, in SV-COMP'25, RacerF relies on the Frama-C's abstract interpreter EVA to perform the analysis of the sequential behaviour. Although RacerF does not provide any formal guarantees, it ranked second in the NoDataRace-Main sub-category, providing the largest number of correct results (when excluding metaverifiers) and just 4 false positives.en
dc.description.abstractRacerF is a static analyser for detection of data races in multithreaded C programs implemented as a  plugin of the Frama-C platform. The approach behind RacerF is mostly heuristic and relies on analysis of the sequential behaviour of particular threads whose results are generalised using a combination of under- and over-approximating techniques to allow analysis of the multithreading behaviour. In particular, in SV-COMP'25, RacerF relies on the Frama-C's abstract interpreter EVA to perform the analysis of the sequential behaviour. Although RacerF does not provide any formal guarantees, it ranked second in the NoDataRace-Main sub-category, providing the largest number of correct results (when excluding metaverifiers) and just 4 false positives.en
dc.formattextcs
dc.format.extent248-253cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationProceedings of the 31st International Conference on Tools and Algorithms for the Construction and Analysis of Systems, part 3. 2025, vol. 15698, p. 248-253.en
dc.identifier.doi10.1007/978-3-031-90660-2_20cs
dc.identifier.isbn978-3-031-90659-6cs
dc.identifier.orcid0000-0003-4083-8943cs
dc.identifier.orcid0000-0002-2746-8792cs
dc.identifier.other198081cs
dc.identifier.researcheridK-5057-2015cs
dc.identifier.scopus8727483800cs
dc.identifier.urihttps://hdl.handle.net/11012/255590
dc.language.isoencs
dc.publisherSpringer Nature Switzerland AGcs
dc.relation.ispartofProceedings of the 31st International Conference on Tools and Algorithms for the Construction and Analysis of Systems, part 3cs
dc.relation.urihttps://link.springer.com/content/pdf/10.1007/978-3-031-90660-2_20.pdfcs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectdata raceen
dc.subjectdata race detectionen
dc.subjectstatic analysisen
dc.subjectprogram verificationen
dc.subjectSV-COMPen
dc.subjectdata race
dc.subjectdata race detection
dc.subjectstatic analysis
dc.subjectprogram verification
dc.subjectSV-COMP
dc.titleRacerF: Data Race Detection with Frama-C (Competition Contribution)en
dc.title.alternativeRacerF: Data Race Detection with Frama-C (Competition Contribution)en
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.grantNumberinfo:eu-repo/grantAgreement/GA0/GA/GA23-06506Scs
sync.item.dbidVAV-198081en
sync.item.dbtypeVAVen
sync.item.insts2025.10.21 09:05:37en
sync.item.modts2025.10.21 08:32:52en
thesis.grantorVysoké učení technické v Brně. Fakulta informačních technologií. Ústav inteligentních systémůcs
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