文章基本信息

标题：ML-CLUBAS: A Multi Label Bug Classification Algorithm
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作者：Naresh Kumar Nagwani ; Shrish Verma
期刊名称：Journal of Software Engineering and Applications
印刷版ISSN：1945-3116
电子版ISSN：1945-3124
出版年度：2012
卷号：5
期号：12
页码：983-990
DOI：10.4236/jsea.2012.512113
出版社：Scientific Research Publishing
摘要：In this paper, a multi label variant of CLUBAS [1] algorithm, ML-CLUBAS (Multi Label-Classification of software Bugs Using Bug Attribute Similarity) is presented. CLUBAS is a hybrid algorithm, and is designed by using text clustering, frequent term calculations and taxonomic terms mapping techniques, and is an example of classification using clustering technique. CLUBAS is a single label algorithm, where one bug cluster is exactly mapped to a single bug category. However a bug cluster can be mapped into the more than one bug category in case of cluster label matches with the more than one category term, for this purpose ML-CLUBAS a multi label variant of CLUBAS is presented in this work. The designed algorithm is evaluated using the performance parameters F-measures and accuracy, number of clusters and purity. These parameters are compared with the CLUBAS and other multi label text clustering algorithms.
关键词：Software Bug Mining; Software Bug Classification; Bug Clustering; Classification Using Clustering; Bug Attribute Similarity; Multi Label Classification