ACM Computing Surveys (CSUR) - Special issue: position statements on strategic directions in computing research
Predicting Fault Incidence Using Software Change History
IEEE Transactions on Software Engineering
Use of relative code churn measures to predict system defect density
Proceedings of the 27th international conference on Software engineering
On the Automatic Modularization of Software Systems Using the Bunch Tool
IEEE Transactions on Software Engineering
Predicting fault-prone components in a java legacy system
Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering
Mining Aspects from Version History
ASE '06 Proceedings of the 21st IEEE/ACM International Conference on Automated Software Engineering
Do Crosscutting Concerns Cause Defects?
IEEE Transactions on Software Engineering
Predicting faults using the complexity of code changes
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
On the Relationship Between Change Coupling and Software Defects
WCRE '09 Proceedings of the 2009 16th Working Conference on Reverse Engineering
High-impact defects: a study of breakage and surprise defects
Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering
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Software change history plays an important role in measuring software quality and predicting defects. Co-change metrics such as number of files changed together has been used as a predictor of bugs. In this study, we further investigate the impact of specific characteristics of co-change dispersion on software quality. Using statistical regression models we show that co-changes that include files from different subsystems result in more bugs than co-changes that include files only from the same subsystem. This can be used to improve bug prediction models based on co-changes.