Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/244807
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dc.titleConcurrency-related Flaky Test Detection in Android apps.
dc.contributor.authorDong, Zhen
dc.contributor.authorTiwari, Abhishek
dc.contributor.authorYu, Xiao Liang
dc.contributor.authorRoychoudhury, Abhik
dc.date.accessioned2023-09-04T01:35:54Z
dc.date.available2023-09-04T01:35:54Z
dc.date.issued2020
dc.identifier.citationDong, Zhen, Tiwari, Abhishek, Yu, Xiao Liang, Roychoudhury, Abhik (2020). Concurrency-related Flaky Test Detection in Android apps.. CoRR abs/2005.10762. ScholarBank@NUS Repository.
dc.identifier.issn2331-8422
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/244807
dc.description.abstractValidation of Android apps via testing is difficult owing to the presence of flaky tests. Due to non-deterministic execution environments, a sequence of events (a test) may lead to success or failure in unpredictable ways. In this work, we present an approach and tool FlakeShovel for detecting flaky tests through systematic exploration of event orders. Our key observation is that for a test in a mobile app, there is a testing framework thread which creates the test events, a main User-Interface (UI) thread processing these events, and there may be several other background threads running asynchronously. For any event e whose execution involves potential non-determinism, we localize the earliest (latest) event after (before) which e must happen.We then efficiently explore the schedules between the upper/lower bound events while grouping events within a single statement, to find whether the test outcome is flaky. We also create a suite of subject programs called DroidFlaker to study flaky tests in Android apps. Our experiments on subject-suite DroidFlaker demonstrate the efficacy of our flaky test detection. Our work is complementary to existing flaky test detection tools like Deflaker which check only failing tests. FlakeShovel can detect flaky tests among passing tests, as shown by our approach and experiments.
dc.sourceElements
dc.subjectcs.SE
dc.subjectcs.SE
dc.typeArticle
dc.date.updated2023-09-03T10:36:50Z
dc.contributor.departmentDEPARTMENT OF COMPUTER SCIENCE
dc.description.sourcetitleCoRR
dc.description.volumeabs/2005.10762
dc.published.statePublished
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