SemDiff: Analysis and recommendation support for API evolution
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
Recommending change clusters to support software investigation: an empirical study
Journal of Software Maintenance and Evolution: Research and Practice - Working Conference on Reverse Engineering (WCRE 2008)
Recommending Adaptive Changes for Framework Evolution
ACM Transactions on Software Engineering and Methodology (TOSEM)
Empirical Software Engineering
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During software maintenance tasks, developers often spend an important amount of effort investigating source code. This effort can be reduced if tools are available to help developers navigate the source code effectively. For this purpose, we propose to search the change history of a software system to identify clusters of program elements related to a task. We evaluated the feasibility of this idea with an extensive historical analysis of change data. Our study evaluated to what extent change sets approximating tasks could have benefited from knowledge about clusters of past changes. A study of 3 500 change sets for seven different systems and covering a cumulative time span of close to 12 years of development shows that less than 12% of the changes could have benefited from change clusters. We report on our observations on the factors that influence how we can use change clusters to guide program navigation.