Adaptive Self-Organizing Map Clustering for Software Fault Prediction
نویسندگان
چکیده
This paper presents a new approach for predicting software faults by means of two-level clustering with unknown number of clusters. We employed Self-Organizing Map method and our proposed clustering approach in the first and second level, respectively, to classify historical and development data into clusters. Next we applied the Radial-Basis Function Network to predict software faults occurred in cluster components. In so doing, we were able to predict software faults reasonably accurate.
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تاریخ انتشار 2007