Change Bursts as Defect Predictors

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...

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Bibliographic Details
Main Authors: Nagappan, Nachiappan, Zeller, Andreas, Zimmermann, Thomas, Herzig, Kim, Murphy, Brendan
Format: Conference Proceeding
Language:English
Subjects:
change history
Complexity theory
defects
developers
empirical studies
History
Measurement
Predictive models
Process metrics
product metrics
Programming
Quality assurance
Software
software mining
software quality assurance
version control
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Summary: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.
ISSN:1071-9458
2332-6549
DOI:10.1109/ISSRE.2010.25