Extracting structural information from bug reports

In software engineering experiments, the description of bug reports is typically treated as natural language text, although it often contains stack traces, source code, and patches. Neglecting such structural elements is a loss of valuable information; structure usually leads to a better performance...

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Bibliographic Details
Main Authors: Bettenburg, Nicolas, Premraj, Rahul, Zimmermann, Thomas, Kim, Sunghun
Format: Conference Proceeding
Language:English
Subjects:
Software and its engineering > Software creation and management > Software post-development issues > Maintaining software
Software and its engineering > Software creation and management > Software verification and validation
Software and its engineering > Software organization and properties > Software functional properties > Correctness
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Summary:In software engineering experiments, the description of bug reports is typically treated as natural language text, although it often contains stack traces, source code, and patches. Neglecting such structural elements is a loss of valuable information; structure usually leads to a better performance of machine learning approaches. In this paper, we present a tool called infoZilla that detects structural elements from bug reports with near perfect accuracy and allows us to extract them. We anticipate that infoZilla can be used to leverage data from bug reports at a different granularity level that can facilitate interesting research in the future.
ISSN:0270-5257
DOI:10.1145/1370750.1370757