Evolution Slicing-Based Change Impact Analysis
Wanzhi Wen, Jianping Chen, Yuan Jiaqi, Xiaoyong Chen · 2017
Generally, software evolution activity is a process of frequent iteration which produces large-volume, heterogeneous and unstructured data in a fast way. During this process, lots of noisy data and side effects are generated. In this way, these software evolution data form the so called four Vs of Big Data. So it is necessary to extract valuable information from the big software evolution data in order to carry out an effective change impact analysis to assure safe evolution process. This paper proposes a change impact analysis technique based on evolution slicing to tackle such big software evolution data at the code level. This technique firstly distinguishes the modified elements, and then constructs the evolution slice to assist software developers and maintainers to make evolution decisions. The experiment on four simple example programs shows that this technique has a better recall value.