Mining A change history to quickly identify bug locations : A case study of the Eclipse project

In this study, we proposed an approach to mine a change history to improve the bug localization performance. The key idea is that a recently fixed file may be fixed in the near future. We used a combination of textual feature and mining the change history to recommend source code files that are likely to be fixed for a given bug report. First, we adopted the Vector Space Model (VSM) to find relevant source code files that are textually similar to the bug report. Second, we analyzed the change history to identify previously fixed files. We then estimated the fault proneness of these files. Finally, we combined the two scores, from textual similarity and fault proneness, for every source code file. We then recommend developers examine source code files with higher scores. We evaluated our approach based on 1,212 bug reports from the Eclipse Platform and Eclipse JDT. The experimental results show that our proposed approach can improve the bug localization performance and effectively identify buggy files.