Abstract
Although software reliability can be evaluated by applying data mining techniques in softwareengineering data to identify software defects or faults, it is difficult to select the best algorithm among the numerous data mining techniques. The goal of this paper is to propose a multiple criteria decision making (MCDM) framework for data mining algorithms selection in software reliability management. Through the application of MCDM method, this paper compares experimentally the performance ofseveral popular data mining algorithms using 13 different performance metrics over 10 public domainsoftware defect datasets from the NASA Metrics Data Program (MDP) repository. The results of theMCDM methods agree on top-ranked classification algorithms and differ about some classifiers forsoftware defect datasets.