The Influence of Developer Quality on Software Fault-Proneness Prediction

Abstract

Previous studies have shown that process metrics are useful for building fault-proneness prediction models. In particular, it has been found that those process metrics incorporating developer experience (defined as the percentage of the code a developer contributes) exhibit a good ability to predict fault-proneness. However, developer quality, which we strongly believe should have a great influence on software quality, is surprisingly ignored. In this paper, we first quantify the quality of a developer via the percentage of history bug-introduce commits over all his/her commits during the development process. Then, we leverage developer quality information to develop eight file quality metrics. Finally, we empirically study the usefulness of these eight file quality metrics for fault-proneness prediction. Based on eight open source software systems, our experiment results show that: 1) these proposed file quality metrics capture additional information compared with existing process metrics, 2) almost all the proposed file quality metrics have a significant association with fault-proneness in an expected direction, and 3) the proposed file quality metrics can in general improve the effectiveness of fault-proneness prediction models when together used with existing process metrics. These results suggest that developer quality has a strong influence on software quality and should be taken into account when predicting software fault-proneness.