MSR '05 Proceedings of the 2005 international workshop on Mining software repositories
YALE: rapid prototyping for complex data mining tasks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Predicting component failures at design time
Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Data Mining Static Code Attributes to Learn Defect Predictors
IEEE Transactions on Software Engineering
Predicting Defects for Eclipse
PROMISE '07 Proceedings of the Third International Workshop on Predictor Models in Software Engineering
Improving defect prediction using temporal features and non linear models
Ninth international workshop on Principles of software evolution: in conjunction with the 6th ESEC/FSE joint meeting
Change Distilling: Tree Differencing for Fine-Grained Source Code Change Extraction
IEEE Transactions on Software Engineering
Proceedings of the 30th international conference on Software engineering
Empirical Software Engineering
IEEE Transactions on Software Engineering
Can developer-module networks predict failures?
Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software engineering
Change Analysis with Evolizer and ChangeDistiller
IEEE Software
Fair and balanced?: bias in bug-fix datasets
Proceedings of the the 7th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
Studying the impact of dependency network measures on software quality
ICSM '10 Proceedings of the 2010 IEEE International Conference on Software Maintenance
Theil index for aggregation of software metrics values
ICSM '10 Proceedings of the 2010 IEEE International Conference on Software Maintenance
Comparing fine-grained source code changes and code churn for bug prediction
Proceedings of the 8th Working Conference on Mining Software Repositories
Replicating mining studies with SOFAS
Proceedings of the 10th Working Conference on Mining Software Repositories
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The Gini coefficient is a prominent measure to quantify the inequality of a distribution. It is often used in the field of economy to describe how goods, e.g., wealth or farmland, are distributed among people. We use the Gini coefficient to measure code ownership by investigating how changes made to source code are distributed among the developer population. The results of our study with data from the Eclipse platform show that less bugs can be expected if a large share of all changes are accumulated, i.e., carried out, by relatively few developers.