Detecting Buggy Files based on Bug Reports: A Random Walk Based Approach

During an Open Source Software (OSS) maintenance, bug localization is a laborsome and time-consuming work for geographically-separated developers. It is desirable to automatically identify related buggy files once a bug report is submitted. Existing work has proposed information retrieval techniques for this problem. However, these proposals tend to neglect the inherent structure in bug localization and they are largely dependent on the comments (annotations) in source files which may be unavailable. In this paper, we propose a random walk based approach to detecting buggy source files based on bug reports. In particular, we separately process source files and bug reports to make it less sensitive to comments, and then apply random walk to capture the inherent structure in bug localization. Experimental evaluations on three real-world open-source projects demonstrate that the proposed approach can outperform several existing methods and that it is less dependent on the comments in source files.