BugFix: A learning-based tool to assist developers in fixing bugs

We present a tool called BugFix that can assist developers in fixing program bugs. Our tool automatically analyzes the debugging situation at a statement and reports a prioritized list of relevant bug-fix suggestions that are likely to guide the developer to an appropriate fix at that statement. BugFix incorporates ideas from machine learning to automatically learn from new debugging situations and bug fixes over time. This enables more effective prediction of the most relevant bug-fix suggestions for newlyencountered debugging situations. The tool takes into account the static structure of a statement, the dynamic values used at that statement by both passing and failing runs, and the interesting value mapping pairs [17] associated with that statement. We present a case study illustrating the efficacy of BugFix in helping developers to fix bugs.

• Type: Conference
• Year: 2009
• Where: IWPC
• Authors: Dennis Jeffrey, Min Feng, Neelam Gupta, Rajiv Gupta
• Keywords: BugFix, Debugging Situations, IWPC 2009, Relevant Bug-fix Suggestions, Software Engineering