In this paper, a multi label variant of CLUBAS  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.
Cite this paper
N. Nagwani and S. Verma, "ML-CLUBAS: A Multi Label Bug Classification Algorithm," Journal of Software Engineering and Applications
, Vol. 5 No. 12, 2012, pp. 983-990. doi: 10.4236/jsea.2012.512113
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