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dc.contributor.authorSchott, Stefan
dc.contributor.authorPauck, Felix
dc.contributor.editorEngels, Gregor
dc.contributor.editorHebig, Regina
dc.contributor.editorTichy, Matthias
dc.date.accessioned2023-01-18T13:38:49Z
dc.date.available2023-01-18T13:38:49Z
dc.date.issued2023
dc.identifier.isbn978-3-88579-726-5
dc.identifier.issn1617-5468
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/40107
dc.description.abstractThe conventional approach of assessing the performance of Android taint analysis tools consists of applying the tool to already existing benchmarks and calculating its performance on the contained benchmark cases. Creating and maintaining a benchmark requires a lot of effort, since it needs to comprise various analysis challenges, and since each benchmark case needs a well documented ground-truth - otherwise one cannot know whether a tool’s analysis is accurate. This effort is further increased by the frequently changing Android API. All these factors lead to the same, usually manually created, benchmarks being reused over and over again. In consequence analysis tools are often over-adapted to these benchmarks. To overcome these issues we propose the concept of benchmark fuzzing , which allows the generation of previously unknown and unique benchmarks, alongside their ground-truths, at evaluation time. We implement this approach in our tool GenBenchDroid and additionally show that we are able to find analysis faults that remain uncovered when solely relying on the conventional benchmarking approach.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofSoftware Engineering 2023
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-332
dc.subjectFuzzing
dc.subjectBenchmarks
dc.subjectAndroid Taint Analysis
dc.titleGenBenchDroid: Fuzzing Android Taint Analysis Benchmarksen
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages107-108
mci.conference.sessiontitleWissenschaftliches Hauptprogramm
mci.conference.locationPaderborn
mci.conference.date20.–24. Februar 2023


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