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dc.contributor.authorHerzig, Kim
dc.contributor.authorJust, Sascha
dc.contributor.authorZeller, Andreas
dc.contributor.editorAßmann, Uwe
dc.contributor.editorDemuth, Birgit
dc.contributor.editorSpitta, Thorsten
dc.contributor.editorPüschel, Georg
dc.contributor.editorKaiser, Ronny
dc.date.accessioned2017-06-30T20:56:09Z
dc.date.available2017-06-30T20:56:09Z
dc.date.issued2015
dc.identifier.isbn978-3-88579-633-6
dc.identifier.issn1617-5468
dc.description.abstractThis submission presents work submitted and accepted at the International onference on Software Engineering in 2013 [Hj2013]. In empirical software engineering, it has become common to mine historic data to detect where bugs have occurred in the past, or to predict where they will occur in the future. The accuracy of such models depends on the quality of the data. For example, defect prediction models rely on the accuracy of historic data, such as bug reports.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofSoftware-engineering and management 2015
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-239
dc.titleIt's not a bug, it's a feature: how misclassification impacts bug predictionen
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages103-104
mci.conference.locationDresden
mci.conference.date17.-20. März 2015


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