Predicting Faults from Cached History

We analyze the version history of 7 software systems to predict the most fault prone entities and files. The basic assumption is that faults do not occur in isolation, but rather in bursts of several related faults. Therefore, we cache locations that are likely to have faults: starting from the loca...

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Bibliographic Details
Main Authors: Kim, Sunghun, Zimmermann, Thomas, Whitehead Jr, E. James, Zeller, Andreas
Format: Conference Proceeding
Language:English
Subjects:
Fault detection
Fault diagnosis
General and reference > Cross-computing tools and techniques > Metrics
General and reference > Cross-computing tools and techniques > Verification
History
Isolation technology
Open source software
Prediction algorithms
Social and professional topics > Professional topics > Management of computing and information systems > Software management
Software algorithms
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 organization and properties > Software functional properties > Formal methods > Software verification
Software quality
Software systems
Switches
Theory of computation > Semantics and reasoning > Program reasoning > Program verification
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Summary:We analyze the version history of 7 software systems to predict the most fault prone entities and files. The basic assumption is that faults do not occur in isolation, but rather in bursts of several related faults. Therefore, we cache locations that are likely to have faults: starting from the location of a known (fixed) fault, we cache the location itself, any locations changed together with the fault, recently added locations, and recently changed locations. By consulting the cache at the moment a fault is fixed, a developer can detect likely fault-prone locations. This is useful for prioritizing verification and validation resources on the most fault prone files or entities. In our evaluation of seven open source projects with more than 200,000 revisions, the cache selects 10% of the source code files; these files account for 73%-95% of faults-- a significant advance beyond the state of the art.
ISSN:0270-5257
1558-1225
DOI:10.1109/ICSE.2007.66