Abstract
Software fault feature analysis has been the important part of software security property analysis and modeling. In this paper, a software fault feature clustering algorithm based on sequence pattern (SFFCSP) is proposed. In SFFCSP, Fault feature matrix is defined to store the relation between the fault feature and the existing sequence pattern. The optimal number of clusters is determined through computing the improved silhouette of fault feature matrix row vector, which corresponds to the software fault feature. In the agglomerative hierarchical clustering phase, entropy is considered as the similarity metric. In order to improve the time complexity of the software fault feature analysis, the fault features of the software to be analyzed are matched to each centroid of clustering results. Experimental results show that SFFCSP has better clustering accuracy and lower time complexity compared with the SEQOPTICS.
This work is supported by the National High Technology Research and Development Program ("863"Program) of China (No. 2009AA01Z433) and the Natural Science Foundation of Hebei Province P.R. China (No.F2008000888).
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Ren, J., Hu, C., Wang, K., Zhang, D. (2009). Software Fault Feature Clustering Algorithm Based on Sequence Pattern. In: Liu, W., Luo, X., Wang, F.L., Lei, J. (eds) Web Information Systems and Mining. WISM 2009. Lecture Notes in Computer Science, vol 5854. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05250-7_46
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DOI: https://doi.org/10.1007/978-3-642-05250-7_46
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