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Bflinks: Reliable Bugfix Links via Bidirectional References and Tuned Heuristics

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 metad...

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Autores principales: Prechelt, Lutz, Pepper, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4897393/
https://www.ncbi.nlm.nih.gov/pubmed/27433506
http://dx.doi.org/10.1155/2014/701357
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author Prechelt, Lutz
Pepper, Alexander
author_facet Prechelt, Lutz
Pepper, Alexander
author_sort Prechelt, Lutz
collection PubMed
description 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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spelling pubmed-48973932016-07-18 Bflinks: Reliable Bugfix Links via Bidirectional References and Tuned Heuristics Prechelt, Lutz Pepper, Alexander Int Sch Res Notices Research Article 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. Hindawi Publishing Corporation 2014-10-29 /pmc/articles/PMC4897393/ /pubmed/27433506 http://dx.doi.org/10.1155/2014/701357 Text en Copyright © 2014 L. Prechelt and A. Pepper. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Prechelt, Lutz
Pepper, Alexander
Bflinks: Reliable Bugfix Links via Bidirectional References and Tuned Heuristics
title Bflinks: Reliable Bugfix Links via Bidirectional References and Tuned Heuristics
title_full Bflinks: Reliable Bugfix Links via Bidirectional References and Tuned Heuristics
title_fullStr Bflinks: Reliable Bugfix Links via Bidirectional References and Tuned Heuristics
title_full_unstemmed Bflinks: Reliable Bugfix Links via Bidirectional References and Tuned Heuristics
title_short Bflinks: Reliable Bugfix Links via Bidirectional References and Tuned Heuristics
title_sort bflinks: reliable bugfix links via bidirectional references and tuned heuristics
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4897393/
https://www.ncbi.nlm.nih.gov/pubmed/27433506
http://dx.doi.org/10.1155/2014/701357
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