Search Results for « Fault Localization »

This paper describes a new technique, which automatically selects the most appropriate developers for fixing the fault represented by a failing test case, and provides a diagnosis of where to look for the fault. This technique works by incorporating three key components: (1) fault localization to inform locations whose execution correlate with failure, (2) history mining to inform which developers edited each line of code and when, and (3) expertise assignment to map locations to developers. To our knowledge, the technique is the first to assign developers to execution failures, without the need for textual bug reports. We implement this technique in our tool, WHOSEFAULT, and describe an experiment where we utilize a large, open-source project to determine the frequency in which our tool suggests an assignment to the actual developer who fixed the fault. Our results show that 81% of the time, WHOSEFAULT produced the same developer that actually fixed the fault within the top three suggestions. We also show that our technique improved by a difference between 4% and 40% the results of a baseline technique. Finally, we explore the influence of each of the three components of our technique over its results, and compare our expertise algorithm against an existing expertise assessment technique and find that our algorithm provides greater accuracy, by up to 37%.