Software Change Impact Analysis
Software Change Impact Analysis
CVS Release History Data for Detecting Logical Couplings
IWPSE '03 Proceedings of the 6th International Workshop on Principles of Software Evolution
Predicting Source Code Changes by Mining Change History
IEEE Transactions on Software Engineering
Mining Version Histories to Guide Software Changes
IEEE Transactions on Software Engineering
MSR '05 Proceedings of the 2005 international workshop on Mining software repositories
Impact Analysis by Mining Software and Change Request Repositories
METRICS '05 Proceedings of the 11th IEEE International Software Metrics Symposium
Fine-Grained Analysis of Change Couplings
SCAM '05 Proceedings of the Fifth IEEE International Workshop on Source Code Analysis and Manipulation
Mining a Change-Based Software Repository
MSR '07 Proceedings of the Fourth International Workshop on Mining Software Repositories
Combining Single-Version and Evolutionary Dependencies for Software-Change Prediction
MSR '07 Proceedings of the Fourth International Workshop on Mining Software Repositories
Change Distilling: Tree Differencing for Fine-Grained Source Code Change Extraction
IEEE Transactions on Software Engineering
A Bayesian Network Based Approach for Change Coupling Prediction
WCRE '08 Proceedings of the 2008 15th Working Conference on Reverse Engineering
Discovering Patterns of Change Types
ASE '08 Proceedings of the 2008 23rd IEEE/ACM International Conference on Automated Software Engineering
Towards a classification of logical dependencies origins: a case study
Proceedings of the 12th International Workshop on Principles of Software Evolution and the 7th annual ERCIM Workshop on Software Evolution
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Change impact analysis plays an immanent role in the maintenance and enhancement of software systems. There still exist many approaches to support change impact analysis. In the last years researchers try to utilize data in software repositories to gain findings for supporting miscellaneous aspects of software engineering, e.g. software evolution analysis or change impact analysis. In the context of change impact analysis, approaches (=strategies) try to detect logical dependencies among artifacts based on the version histories of files in the concurrent versioning system (e.g. CVS). They try to infer logical couplings of files (artifacts) based on co-changes (files which are frequently changed together). Based on these findings we want to contribute with the presentation of insights of deeper investigation of historical information in concurrent versioning systems in general. In this paper we have identified and described existing strategies to detect logical change couplings. These strategies will be illustrated by practical use cases. We have empirically evaluated these strategies based on versioning system repositories of two industrial projects. The analysis figures the absolute and relative contribution of dependency results per strategy. Furthermore we show overlappings of dependency results.