Automating Root Cause Analysis via Machine Learning in Agile Software Testing Environments

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorKahles, Julenen_US
dc.contributor.authorTorronen, Juhaen_US
dc.contributor.authorHuuhtanen, Timoen_US
dc.contributor.authorJung, Alexanderen_US
dc.contributor.departmentEricsson Finlanden_US
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.contributor.departmentHelsinki Institute for Information Technology (HIIT)en_US
dc.date.accessioned2019-08-15T08:19:51Z
dc.date.available2019-08-15T08:19:51Z
dc.date.issued2019-04-01en_US
dc.description.abstractWe apply machine learning to automate the root cause analysis in agile software testing environments. In particular, we extract relevant features from raw log data after interviewing testing engineers (human experts). Initial efforts are put into clustering the unlabeled data, and despite obtaining weak correlations between several clusters and failure root causes, the vagueness in the rest of the clusters leads to the consideration of labeling. A new round of interviews with the testing engineers leads to the definition of five ground-truth categories. Using manually labeled data, we train artificial neural networks that either classify the data or pre-process it for clustering. The resulting method achieves an accuracy of 88.9%. The methodology of this paper serves as a prototype or baseline approach for the extraction of expert knowledge and its adaptation to machine learning techniques for root cause analysis in agile environments.en
dc.description.versionPeer revieweden
dc.format.extent12
dc.format.extent379-390
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationKahles , J , Torronen , J , Huuhtanen , T & Jung , A 2019 , Automating Root Cause Analysis via Machine Learning in Agile Software Testing Environments . in Proceedings - 2019 IEEE 12th International Conference on Software Testing, Verification and Validation, ICST 2019 . , 8730163 , IEEE , pp. 379-390 , IEEE International Conference on Software Testing, Verification and Validation , Xi'an , China , 22/04/2019 . https://doi.org/10.1109/ICST.2019.00047en
dc.identifier.doi10.1109/ICST.2019.00047en_US
dc.identifier.isbn9781728117355
dc.identifier.otherPURE UUID: 05cf4c87-41ac-400b-9bae-e34838c4d2b9en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/05cf4c87-41ac-400b-9bae-e34838c4d2b9en_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85067984205&partnerID=8YFLogxKen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/35606292/SCI_Kahles_Torronen_Huuhtanen_Jung_Automating_Root_2019_RCA_ML_SW.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/39608
dc.identifier.urnURN:NBN:fi:aalto-201908154653
dc.language.isoenen
dc.relation.ispartofIEEE International Conference on Software Testing, Verification and Validationen
dc.relation.ispartofseriesProceedings - 2019 IEEE 12th International Conference on Software Testing, Verification and Validation, ICST 2019en
dc.rightsopenAccessen
dc.subject.keywordArtificial neural networksen_US
dc.subject.keywordAutomationen_US
dc.subject.keywordClassificationen_US
dc.subject.keywordClusteringen_US
dc.subject.keywordLog data analysisen_US
dc.subject.keywordMachine learningen_US
dc.subject.keywordRoot cause analysisen_US
dc.subject.keywordSoftware testingen_US
dc.titleAutomating Root Cause Analysis via Machine Learning in Agile Software Testing Environmentsen
dc.typeConference article in proceedingsfi
dc.type.versionacceptedVersion
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