Using patterns position distribution for software failure detection

Li, Chunping, Chen, Ziniu, Du, Hao, Wang, Hui, Wilkie, George, Augusto, Juan Carlos ORCID logoORCID: https://orcid.org/0000-0002-0321-9150 and Liu, Jun (2013) Using patterns position distribution for software failure detection. International Journal of Computational Intelligence Systems, 6 (2) . pp. 234-243. ISSN 1875-6891 [Article] (doi:10.1080/18756891.2013.768442)

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Abstract

Pattern-based software failure detection is an important topic of research in recent years. In this method, a set of patterns from program execution traces are extracted, and represented as features, while their occurrence frequencies are treated as the corresponding feature values. But this conventional method has its limitation due to ignore the pattern’s position information, which is important for the classification of program traces. Patterns occurs in the different positions of the trace are likely to represent different meanings. In this paper, we present a novel approach for using pattern’s position distribution as features to detect software failure. The comparative experiments in both artificial and real datasets show the effectiveness of this method.

Item Type: Article
Research Areas: A. > School of Science and Technology > Computer Science > Intelligent Environments group
A. > School of Science and Technology > Computer Science
Item ID: 9979
Useful Links:
Depositing User: Dr. Juan C. Augusto
Date Deposited: 03 Apr 2013 11:57
Last Modified: 30 Nov 2022 00:13
URI: https://eprints.mdx.ac.uk/id/eprint/9979

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