COMPARATIVE ANALYSIS OF CLASSIFICATION METHODS FOR PREDICTION SOFTWARE FAULT PRONENESS USING PROCESS METRICS

As we all know a lot of research has been done in the field of software defect prediction but most of them uses static code metrics as their independent variable. In this paper the main objective is to analyze the effect of process metrics on prediction performance using various classification and ensemble techniques. Also in this i have used both AUC and MCC measure to analyze the results. We can conclude that process metrics are as effective as static code metrics.