Reducing Features to Improve Bug Prediction

Recently, machine learning classifiers have emerged as a way to predict the existence of a bug in a change made to a source code file. The classifier is first trained on software history data, and then used to predict bugs. Two drawbacks of existing classifier-based bug prediction are potentially in...

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Bibliographische Detailangaben
Hauptverfasser:	Shivaji, Shivkumar, Jr, E. James Whitehead, Akella, Ram, Kim, Sunghun
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Bug prediction Computer bugs Computing methodologies > Machine learning > Learning paradigms > Supervised learning > Supervised learning by classification Computing methodologies > Machine learning > Machine learning algorithms > Feature selection Computing methodologies > Machine learning > Machine learning approaches > Classification and regression trees Design engineering Feature Selection General and reference > Cross-computing tools and techniques > Verification History Machine learning Prediction algorithms Reliability Scalability Software and its engineering > Software creation and management > Software development process management Software and its engineering > Software creation and management > Software verification and validation > Formal software verification Software and its engineering > Software creation and management > Software verification and validation > Software defect analysis > Software testing and debugging Software and its engineering > Software organization and properties > Software functional properties > Formal methods > Software verification Software engineering Software performance Support vector machine classification Support vector machines Theory of computation > Semantics and reasoning > Program reasoning > Program verification
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