Sciweavers

TSE
2008

Benchmarking Classification Models for Software Defect Prediction: A Proposed Framework and Novel Findings

13 years 2 months ago
Benchmarking Classification Models for Software Defect Prediction: A Proposed Framework and Novel Findings
Software defect prediction strives to improve software quality and testing efficiency by constructing predictive classification models from code attributes to enable a timely identification of fault-prone modules. Several classification models have been evaluated for this task. However, due to inconsistent findings regarding the superiority of one classifier over another and the usefulness of metric-based classification in general, more research is needed to improve convergence across studies and further advance confidence in experimental results. We consider three potential sources for bias: comparing classifiers over one or a small number of proprietary data sets, relying on accuracy indicators that are conceptually inappropriate for software defect prediction and cross-study comparisons, and, finally, limited use of statistical testing procedures to secure empirical findings. To remedy these problems, a framework for comparative software defect prediction experiments is proposed and...
Stefan Lessmann, Bart Baesens, Christophe Mues, Sw
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2008
Where TSE
Authors Stefan Lessmann, Bart Baesens, Christophe Mues, Swantje Pietsch
Comments (0)