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Major motivations for extract method refactorings: analysis based on interviews and change histories

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Abstract

Extract method is one of the most popular software refactorings. However, little work has been done to investigate or validate the major motivations for such refactorings. Digging into this issue might help researchers to improve tool support for extract method refactorings, e.g., proposing better tools to recommend refactoring opportunities, and to select fragments to be extracted. To this end, we conducted an interview with 25 developers, and our results suggest that current reuse, decomposition of long methods, clone resolution, and future reuse are the major motivations for extract method refactorings.We also validated the results by analyzing the refactoring history of seven open-source applications. Analysis results suggest that current reuse was the primary motivation for 56% of extract method refactorings, decomposition of methods was the primary motivation for 28% of extract method refactorings, and clone resolution was the primary motivation for 16% of extract method refactorings. These findings might suggest that recommending extract method opportunities by analyzing only the inner structure (e.g., complexity and length) of methods alone would miss many extract method opportunities. These findings also suggest that extract method refactorings are often driven by current and immediate reuse. Consequently, how to recognize or predict reuse requirements timely during software evolution may play a key role in the recommendation and automation of extract method refactorings. We also investigated the likelihood for the extracted methods to be reused in future, and our results suggest that such methods have a small chance Received April 2, 2015; accepted November 10, 2015 E-mail: Liuhui08@bit.edu.cn (12%) to be reused in future unless the extracted fragment could be reused immediately in software evolution and extracting such a fragment can resolve existing clones at the same time.

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Authors and Affiliations

  1. School of Computer Science and Technology, Beijing Institute of Technology, Beijing, 100081, China

    Wenmei Liu & Hui Liu

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  1. Wenmei Liu
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  2. Hui Liu
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Correspondence to Hui Liu.

Additional information

Wenmei Liu received the BS degree in control science from Shandong University, China in 2003, and the MS degree from Beihang University, China in 2006. She is currently working toward the PhD degree with the School of Computer Science and Technology at the Beijing Institute of Technology, China. Her research interests include software engineering, software refactoring, and software evolution.

Hui Liu received the BS degree in control science from Shandong University, China in 2001, theMS degree in computer science from Shanghai University, China in 2004, and the PhD degree in computer science from Peking University, China in 2008. He is currently an associate professor in the School of Computer Science and Technology at the Beijing Institute of Technology, China. He is particularly interested in software refactoring, design pattern, and software evolution. He is currently doing research to make software refactoring easier and safer. He is also interested in developing practical refactoring tools to assist software engineers.

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Liu, W., Liu, H. Major motivations for extract method refactorings: analysis based on interviews and change histories. Front. Comput. Sci. 10, 644–656 (2016). https://doi.org/10.1007/s11704-016-5131-4

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