Using Fuzzy Clustering and Software Metrics to Predict Faults in large Industrial Software Systems

نویسندگان

  • Nurudeen Sherif
  • Nurudeen Mohammed
چکیده

Faults are a key problem in software systems. Awareness of possible flaws from the initialization of a project could save money, time and work. Estimating the possible deficiency of software could help in executing software development activities. This paper proposes a model to predict the possibility of faults on a software system before testing. The model predicts possible faults during software development using Fuzzy Clustering and Software Metrics. This research is aimed at predicting faults in large software systems by creating clusters and then finding out the distance of each point in the data set with the clusters created to determine their degree of membership within each cluster

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تاریخ انتشار 2013