Predicting Fault-Prone Software Modules with Rank Sum Classification

@article{Cahill2013PredictingFS,
  title={Predicting Fault-Prone Software Modules with Rank Sum Classification},
  author={Jaspar Cahill and James M. Hogan and Richard N. Thomas},
  journal={2013 22nd Australian Software Engineering Conference},
  year={2013},
  pages={211-219}
}
The detection and correction of defects remains among the most time consuming and expensive aspects of software development. Extensive automated testing and code inspections may mitigate their effect, but some code fragments are necessarily more likely to be faulty than others, and automated identification of fault prone modules helps to focus testing and inspections, thus limiting wasted effort and potentially improving detection rates. However, software metrics data is often extremely noisy… CONTINUE READING

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