Software refactoring is widely conducted in the industry and well-studied in the academic community. There are dozens of software refactoring types, and each type of refactoring often requires its unique tool support and algorithms. Consequently, knowing which types of refactorings are popular in real-world practice and which are less supported by existing tools is highly valuable. To this end, in this paper, we present a large-scale empirical study on software refactorings in real-world open-source Java projects. We first retrieved by keywords 15,860 code commits from GitHub that might contain software refactorings. From the resulting commits, we manually analyzed 1,200 of them and successfully identified 100 types of refactorings from 420 commits. We built a taxonomy for the discovered refactorings, and compared them against the refactoring types supported by state-of-the-art refactoring engines and miners. The comparison results suggest that 61 out of the 100 refactoring types have not yet been explicitly supported by any of the refactoring engines, and any refactoring miners have not explicitly supported 62. The empirical study has identified and revealed 31 under-explored refactorings observed in Java real-world open-source applications but not yet supported by existing refactoring tools. These refactorings may have implications for the development of future tool support and enhancements in the refactoring ecosystem.

Software refactoring is to improve readability, maintainability and expansibility of software by adjusting its internal structure, whereas the external behaviors of software are not changed. Although software refactoring should not change the external behaviors of software systems, they might make a regression test case obsolete (with syntax and runtime errors) or fail. People have investigated which refactorings had an influence on regression test case. However, how test cases are influenced by refactorings and what kind of errors might be introduced remain unknown. To this end, in this paper, we proposed an approach to analyze refactorings' impact on regression test cases. On one hand, we analyzed why regression test cases failed. On the other hand, we analyzed the influence of refactorings on software interfaces. Based on the analysis, we built up a mapping between refactorings and test case failure. Such a mapping can be used to guide test case repair automation where test cases are made obsolete by refactorings. The approach was evaluated on five open-source applications. Evaluation results suggest that the precision of the approach is greater than 80%.