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|Title:||Accurately choosing execution runs for software fault localization||Authors:||Guo, L.
|Issue Date:||2006||Citation:||Guo, L.,Roychoudhury, A.,Wang, T. (2006). Accurately choosing execution runs for software fault localization. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 3923 LNCS : 80-95. ScholarBank@NUS Repository.||Abstract:||Software fault localization involves locating the exact cause of error for a "failing" execution run - a run which exhibits an unexpected behavior. Given such a failing run, fault localization often proceeds by comparing the failing run with a "successful" run, that is, a run which does not exhibit the unexpected behavior. One important issue here is the choice of the successful run for such a comparison. In this paper, we propose a control flow based difference metric for this purpose. The difference metric takes into account the sequence of statement instances (and not just the set of these instances) executed in the two runs, by locating branch instances with similar contexts but different outcomes in the failing and the successful runs. Given a failing run π f and a pool of successful runs S, we choose the successful run π s from 5 whose execution trace is closest to π f in terms of the difference metric. A bug report is then generated by returning the difference between π f and π s. We conduct detailed experiments to compare our approach with previously proposed difference metrics. In particular, we evaluate our approach in terms of (a) effectiveness of bug report for locating the bug, (b) size of bug report and (c) size of successful run pool required to make a decent choice of successful run. © Springer-Verlag Berlin Heidelberg 2006.||Source Title:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)||URI:||http://scholarbank.nus.edu.sg/handle/10635/40674||ISBN:||354033050X||ISSN:||03029743|
|Appears in Collections:||Staff Publications|
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