Publikation
Assisting bug Triage in Large Open Source Projects Using Approximate String Matching
Amir Moin; Günter Neumann
In: The Seventh International Conference on Software Engineering Advances. International Conference on Software Engineering Advances (ICSEA-2012), 7th, November 18-23, Lisboa, Portugal, ICSEA, 11/2012.
Zusammenfassung
In this paper, we propose a novel approach for
assisting human bug triagers in large open source software
projects by semi-automating the bug assignment process. Our
approach employs a simple and efficient n-gram-based algorithm
for approximate string matching. We propose and
implement a recommender prototype which collects the natural
language textual information available in the summary and
description fields of the previously resolved bug reports and
classifies that information in a number of separate inverted
lists with respect to the resolver of each issue. These inverted
lists are considered as vocabulary-based expertise and interest
models of the developers. Given a new bug report, the recommender
creates all possible n-grams of the strings, evaluates
their similarities to the available expertise models concerning
a number of well-known string similarity measures, namely
Cosine, Dice, Jaccard and Overlap coefficients. Finally, the top
three developers are recommended as proper candidates for
resolving this new issue. Experimental results on 5200 bug
reports of the Eclipse JDT project show weighted average
precision value of 90.1% and weighted average recall value
of 45.5%.