Exploring topic models in software engineering data analysis: A survey
Xiaobing Sun, Xiangyue Liu, Bin Li, Yucong Duan, Hui Ming Yang, Jiajun Hu · 2016
Topic models are shown to be effective to mine unstructured software engineering (SE) data. In this paper, we give a simple survey of exploring topic models to support various SE tasks between 2003 and 2015. The survey results show that there is an increasing concern in this area. Among the SE tasks, source code comprehension and software history comprehension are the mostly studied, followed by software defects prediction. However, there is still only a few studies on other SE tasks, such as feature location and regression testing.