Active Learning for Software Defect Prediction

Abstract

An active learning method, called Two-stage Active learning algorithm (TAL), is developed for software defect prediction. Combining the clustering and support vector machine techniques, this method improves the performance of the predictor with less labeling effort. Experiments validate its effectiveness.