Toward Practical Application of Program Refactoring

Program refactoring—transforming a program to improve readability, structure, performance, abstraction, maintainability, or other characteristics— is not applied in practice as much as might be desired. Although there are various possible reasons why program refactoring is not so popular, one deterrent is the cost of detecting candidates for refactoring and of choosing the appropriate refactoring transformation. Another problem is that there are few quantitative evaluations of its impact to the software maintainability. It is sometimes difficult to judge whether the refactoring in question should be applied or not without knowing the effect accurately. This series of researches mainly focuses on how to support program refactoring to encourage practical applications of the technique. The first half of this thesis demonstrates the feasibility of automatically finding places in the program that are candidates for specific refactorings. The approach uses program invariants: when particular invariants hold at a program point, a specific refactoring is applicable. Since most programs lack explicit invariants, an invariant detection tool called Daikon is used to infer the required invariants. We developed an invariant pattern matcher for several common refactorings and applied it to an existing Java code base. Numerous refactorings were detected, and one of the developers of the code base assessed their efficacy. The latter half proposes a quantitative evaluation guideline to measure the maintainability enhancement effect of program refactoring. We focused on the module coupling metrics and the module cohesion metrics to evaluate the refactoring effect. Comparing the metrics before and after the refactoring, we could evaluate the degree of maintainability enhancement. As for coupling metrics, we carried out an experiment and found our method was really effective to quantify the refactoring effect and helped us to choose appropriate refactorings.