Mining Version Histories to Guide Software Changes
Proceedings of the 26th International Conference on Software Engineering
Mining Version Histories to Guide Software Changes
IEEE Transactions on Software Engineering
An empirical study of fine-grained software modifications
Empirical Software Engineering
Predicting faults using the complexity of code changes
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
Advances in Software Engineering - Special issue on new generation of software metrics
Toward a version control system for aspect oriented software
MEDI'11 Proceedings of the First international conference on Model and data engineering
Controversy Corner: Preserving knowledge in software projects
Journal of Systems and Software
How changes affect software entropy: an empirical study
Empirical Software Engineering
Bug prediction using entropy-based measures
International Journal of Knowledge Engineering and Data Mining
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In this paper we present a new perspective on the problem of complexity in software, using sound mathematical concepts from information theory such as Shannon's Entropy [31]. We study the complexity of the development process by examining the logs of the source control repository for large software projects. We hypothesize that the process of developing code is a good indicator of the current and future problems in the code and the project. A complex process will have negative affects on its outcome, such as producing a complex system or delaying releases. We validate our work by studying the evolution of six large open source projects (three operating systems, a window manager, an office productivity suite, and a database).