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A Useful Resource for Defect Prediction Models

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons45239

Ragneala,  Roxana
International Max Planck Research School, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45720

Weikum,  Gerhard
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Zitation

Ragneala, R. (2009). A Useful Resource for Defect Prediction Models. Master Thesis, Universität des Saarlandes, Saarbrücken.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0027-BA8D-E
Zusammenfassung
Predicting likely software defects in the future is valuable for project managers when planning resource allocation for software testing. But building prediction models using only code metrics may not be suffice for accurate results. In this work, we investigate the value of code history metrics that can be collected from the project's version archives for the purpose of defect prediction. Our results suggest that prediction models built using code history metrics outperform those using traditional code metrics only.