Abstract
Multiple information retrieval (IR)-based bug localization techniques have been proposed over the last years. The foundation of the approaches relies on textual similarity of the bug report description and the source code files. The basic assumption is that these descriptions are well suited to query the code base. However, often bug reports contain structured information such as stack traces and source code next to natural language, which might interfere with the initial belief. In this paper, we systematically analyze the influence of structured information on IR-based techniques. Therefore, an empirical study on 7334 bug reports, out of which more than 30% contain structured information, was carried out. Based on the results, a follow-up user study was conducted focusing on source code fragments found in bug reports. Our results show that stack traces tend to negatively affect IR-based bug localization performance and require special handling. Compared to natural language–only reports, source code is beneficial for IR-based algorithms, as well as for developers to identify false positives in bug localization results.
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