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

doi:10.1007/s11704-016-5131-4

Front. Comput. Sci.

2016, Vol. 10

Issue (4) : 644-656 https://doi.org/10.1007/s11704-016-5131-4

RESEARCH ARTICLE

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

Wenmei LIU,Hui LIU(

)

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

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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 (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.

Keywords software refactoring extract method motivation data mining software quality

Corresponding Author(s): Hui LIU

Just Accepted Date: 12 November 2015 Online First Date: 12 June 2016 Issue Date: 06 July 2016

Cite this article:

Wenmei LIU,Hui LIU. Major motivations for extract method refactorings: analysis based on interviews and change histories[J]. Front. Comput. Sci., 2016, 10(4): 644-656.

URL:

https://academic.hep.com.cn/fcs/EN/10.1007/s11704-016-5131-4
https://academic.hep.com.cn/fcs/EN/Y2016/V10/I4/644

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