Abstract
The aim has been to detect discriminative sub-graphs which are highly distinguishable between program failing and passing execution graphs resulted from different runs. In this paper, a novel approach to mine weighted-edge graphs is proposed. We also apply our efficient objective function to find most discriminative patterns between failing and passing graphs. To find bug relevant sub-graphs, a decision tree classifier is used to classify program failing and passing runs based on their discriminative sub-graphs. The experimental results on Siemens test suite reveal the effectiveness of the proposed approach specifically in finding multiple bugs. It also gives the debugger an infection path related to the discovered bug(s).
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Parsa, S., Arabi, S., Ebrahimi, N., Vahidi-Asl, M. (2010). Finding Discriminative Weighted Sub-graphs to Identify Software Bugs. In: Das, V.V., et al. Information Processing and Management. BAIP 2010. Communications in Computer and Information Science, vol 70. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12214-9_49
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DOI: https://doi.org/10.1007/978-3-642-12214-9_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12213-2
Online ISBN: 978-3-642-12214-9
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