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Authors: ZSUZSANNA MARIAN, ISTVÁN GERGELY CZIBULA.
VIEW PDF: A STUDY ON SOFTWARE DEFECT PREDICTION USING FUZZY DECISION TREES
In this paper we conduct a study on applying fuzzy decision trees for software defect prediction, investigating the results of varying different parameters, for the FuzzyDT method, introduced in a previous paper. The proposed method uses software metrics and fuzzy decision trees to identify potentially faulty software entities like components, modules, methods, etc. Experiments are performed on five open-source case studies in order to analyze the effect of using different thresholds for the software metrics used to defi ne the fuzzy membership functions as well as using different impurity functions in building the fuzzy decision tree. We also analyse whether using only certain selected software metrics leads to a better performance than using all the software metrics from the data sets.The obtained results confi rm that the fuzzy approach outperforms the crisp one and the results are better than most of the results already reported in the literature for the data sets considered in our evaluation.
2010 Mathematics Subject Classifi cation. 68N99, 68T05.
1998 CR Categories and Descriptors. D.2.7 [Software Engineering]: Distribution,Maintenance, and Enhancement - Restructuring, reverse engineering, and reengineering;D.2.8 [Software Engineering]: Metrics {Product metrics; I.2.6 [Arti cial Intelligence]:Learning { Induction;
Key words and phrases. software defect prediction, software metrics, fuzzy decision trees.
