Heterogeneous Defect Prediction through Correlation-Based Selection of Multiple Source Projects and Ensemble Learning

Heterogeneous defect prediction (HDP) predicts defect-prone modules when the source and target data have heterogeneous metric sets. Although several researchers have tried to improve the performance of HDP, many of them did not suggest selection guidelines of source projects nor handle the class imbalance problem. In this paper, we propose a novel approach to improve the performance further by sel...