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Bflinks: Reliable Bugfix Links via Bidirectional References and Tuned Heuristics
Author(s) -
Lutz Prechelt,
Alexander Pepper
Publication year - 2014
Publication title -
international scholarly research notices
Language(s) - English
Resource type - Journals
ISSN - 2356-7872
DOI - 10.1155/2014/701357
Subject(s) - heuristics , computer science , commit , set (abstract data type) , heuristic , data mining , string (physics) , software , metadata , modular design , matching (statistics) , information retrieval , database , artificial intelligence , programming language , world wide web , statistics , mathematics , operating system , physics , quantum mechanics
Background. Data from software version archives and defect databases can be used for defect insertion circumstance analysis and defect prediction. The first step in such analyses is identifying defect-correcting changes in the version archive (bugfix commits) and enriching them with additional metadata by establishing bugfix links to corresponding entries in the defect database. Candidate bugfix commits are typically identified via heuristic string matching on the commit message. Research Questions. Which filters could be used to obtain a set of bugfix links? How to tune their parameters? What accuracy is achieved? Method. We analyze a modular set of seven independent filters, including new ones that make use of reverse links, and evaluate visual heuristics for setting cutoff parameters. For a commercial repository, a product expert manually verifies over 2500 links to validate the results with unprecedented accuracy. Results. The heuristics pick a very good parameter value for five filters and a reasonably good one for the sixth. The combined filtering, called bflinks, provides 93% precision and only 7% results loss. Conclusion. Bflinks can provide high-quality results and adapts to repositories with different properties.

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