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Bug localization is a tedious activity in the bug fixing process in which asoftware developer tries to locate bugs in the source code described in a bugreport. Since this process is time-consuming and requires additional knowledgeabout the software project, information retrieval techniques can aid the buglocalization process. In this paper, we investigate if normal text searchengines can improve existing bug localization approaches. In a case study, weevaluate the performance of our search engine approach Broccoli against sevenstate-of-the-art bug localization algorithms on 82 open source projects in twodata sets. Our results show that including a search engine can increase theperformance of the bug localization and that it is a useful extension toexisting approaches. As part of our analysis we also exposed a flaw in acommonly used benchmark strategy, i.e., that files of a single release areconsidered. To increase the number of detectable files, we mitigate this flawby considering the state of the software repository at the time of the bugreport. Our results show that using single releases may lead to anunderestimation of the the prediction performance.

Broccoli: Bug localization with the help of text search engines