A method for analyzing fault sequence feature based on clustering

Jiadong Ren*, Changzhen Hu, Kunsheng Wang, Lining Li, Yanpeng Zhang

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

3 引用 (Scopus)

摘要

A large number of fault sequences emerge while analyzing software security,so mining fault sequences is significant for determining the locations ofsoftware faults. In this paper, clustering technology is adopted to analyzefault sequences. In order to cluster unequal-length fault sequences, we proposea new similarity measure and develop a sequence clustering algorithm called CSE(Clustering based on Sequence Elements). In CSE, the number of the mutualsequence elements contained in sequences is calculated to determine thesimilarity of sequences, and fault sequences are collected into clustersaccording to the similarity measure. To analyze the feature of software faults,we introduce a clustering-based method, which combines clustering analysis andsequence alignment. Experimental results show that CSE has higher clusteringquality and good scalability. ICIC International

源语言英语
页(从-至)1087-1092
页数6
期刊ICIC Express Letters
3
4
出版状态已出版 - 12月 2009

指纹

探究 'A method for analyzing fault sequence feature based on clustering' 的科研主题。它们共同构成独一无二的指纹。

引用此