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dc.contributor.authorMöller, Jonas
dc.contributor.editorChristian Wressnegger, Delphine Reinhardt
dc.date.accessioned2023-01-24T11:17:51Z
dc.date.available2023-01-24T11:17:51Z
dc.date.issued2022
dc.identifier.isbn978-3-88579-717-3
dc.identifier.issn1617-5468
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/40143
dc.description.abstractDifferences between programs based on the same specification might lead to vulnerabilities that can not be detected by conventional testing. Differential testing is able to find these discrepancies by executing multiple programs on the same input and comparing their output. In this work, we discuss the fundamentals of differential testing and outline a general scheme for differential testing methods which is used to categorize and analyze current research approaches. Based on this, we formulate our own research questions which focus on how machine learning can aid differential testingen
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofGI SICHERHEIT 2022
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-323
dc.subjectDifferential Testing
dc.subjectFuzzing
dc.titleDifferential Testing: How to find differences between programs that mostly behave identically?en
mci.reference.pages243-248
mci.conference.sessiontitleDoktorand·innenforum
mci.conference.locationKarlsruhe
mci.conference.date5.-8. April 2022
dc.identifier.doi10.18420/sicherheit2022_21
dc.title.subtitleHow to find differences between programs that mostly behave identically?en


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