Change Bursts as Defect Predictors
by Nachiappan Nagappan, Andreas Zeller, Thomas Zimmermann, Kim Herzig, Brendan Murphy

Proceedings of the 21st IEEE International Symposium on Software Reliability Engineering, November 2010.

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Abstract

In software development, every change induces a risk. What happens if code changes again and again in some period of time? In an empirical study on Windows Vista, we found that the features of such change bursts have the highest predictive power for defect-prone components. With precision and recall values well above 90%, change bursts significantly improve upon earlier predictors such as complexity metrics, code churn, or organizational structure. As they only rely on version history and a controlled change process, change bursts are straight-forward to detect and deploy.

BibTeX Entry

@inproceedings{change-bursts-2010,
    title = "Change Bursts as Defect Predictors",
    author = "Nachiappan Nagappan and Andreas Zeller and Thomas Zimmermann and Kim Herzig and Brendan Murphy",
    year = "2010",
    month = nov,
    booktitle = "Proceedings of the 21st IEEE International Symposium on Software Reliability Engineering",
    location = "San Jose, California, USA",
}

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