Software Fault Prediction Using Single Linkage Clustering Method

Until now, various techniques have been proposed for predicting fault prone modules based on prediction performance. Unfortunately quality improvement and cost reduction has been rarely assessed. The main motivation here is optimization of acceptance testing to provide high quality services to customers. From this perspective, the primary goal of this proposed methodology is reduction of acceptance test effort based on fault prediction results using single linkage clustering and simulation model. The prediction is conducted using test dataset and fault prone module are predicted by means of jaccard similarity measure. Simulation model estimates number of discoverable faults and results of simulation showed that the best strategy was to let the test effort be proportional to the number of expected faults in a module multiplied by log(module size).