Conversely, excessive structured information (e.g., stack traces) in the bug report might not always help the automated localization either. Recent findings suggest that Information Retrieval (IR)-based bug localization techniques do not perform well if the bug report lacks rich structured information (e.g., relevant program entity names). These results show the applicability of our approach to software projects without history. Over the projects analysed, on average we find one or more affected files in the top 10 ranked files for 76% of the bug reports. Out of 30 performance indicators, we improve 27 and equal 2. We compare our approach to eight others, using their own five metrics on their own six open source projects.
MUCOMMANDER SIMS 4 MANUAL
The scoring method is based on heuristics identified through manual inspection of a small sample of bug reports. We present a novel approach that directly scores each current file against the given report, thus not requiring past code and reports. However, current state-of-the-art IR approaches rely on project history, in particular previously fixed bugs or previous versions of the source code. Such approaches have the advantage of not requiring expensive static or dynamic analysis of the code. via a bug report, where is it located in the source code? Information retrieval (IR) approaches see the bug report as the query, and the source code files as the documents to be retrieved, ranked by relevance.
Bug localisation is a core program comprehension task in software maintenance: given the observation of a bug, e.g.
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