Network-based analysis of software change propagation.
The object-oriented software systems frequently evolve to meet new change requirements. Understanding the characteristics of changes aids testers and system designers to improve the quality of softwares. Identifying important modules becomes a key issue in the process of evolution. In this context, a novel network-based approach is proposed to comprehensively investigate change distributions and the correlation between centrality measures and the scope of change propagation. First, software dependency networks are constructed at class level. And then, the number of times of cochanges among classes is minded from software repositories. According to the dependency relationships and the number of times of cochanges among classes, the scope of change propagation is calculated. Using Spearman rank correlation analyzes the correlation between centrality measures and the scope of change propagation. Three case studies on java open source software projects Findbugs, Hibernate, and Spring are conducted to research the characteristics of change propagation. Experimental results show that (i) change distribution is very uneven; (ii) PageRank, Degree, and CIRank are significantly correlated to the scope of change propagation. Particularly, CIRank shows higher correlation coefficient, which suggests it can be a more useful indicator for measuring the scope of change propagation of classes in object-oriented software system.
School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430063, China.
Rongcun
R
Wang
School of Computer Science and Telecommunication Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, China.
Rubing
0000-0002-1769-6126
R
Huang
School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430063, China.
Binbin
B
Qu
D016571:Neural Networks, Computer; D012984:Software