Dataset Open Access

How Do I Refactor This? An Empirical Study on Refactoring Trends and Topics in Stack Overflow

Peruma, Anthony; Simmons, Steven; Alomar, Eman Abdullah; Newman, Christian D.; Mkaouer, Mohamed Wiem; Ouni, Ali

This is the dataset that accompanies the study: "How Do I Refactor This? An Empirical Study on Refactoring Trends and Topics in Stack Overflow." This study has been accepted for publication in the software engineering journal Empirical Software Engineering.


Following is the abstract of the study:

An essential part of software maintenance and evolution, refactoring is performed by developers, regardless of technology or domain, to improve the internal quality of the system, and reduce its technical debt. However, choosing the appropriate refactoring strategy is not always straightforward, resulting in developers seeking assistance. Although research in refactoring is well-established, with several studies altering between the detection of refactoring opportunities and the recommendation of appropriate code changes, little is known about their adoption in practice. Analyzing the perception of developers is critical to understand better what developers consider to be problematic in their code and how they handle it. Additionally, there is a need for bridging the gap between refactoring, as research, and its adoption in practice, by extracting common refactoring intents that are more suitable for what developers face in reality. In this study, we analyze refactoring discussions on Stack Overflow through a series of quantitative and qualitative experiments. Our results show that Stack Overflow is utilized by a diverse set of developers for refactoring assistance for a variety of technologies. Our observations show five areas that developers typically require help with refactoring-- Code Optimization, Tools and IDEs, Architecture and Design Patterns, Unit Testing, and Database. We envision our findings better bridge the support between traditional (or academic) aspects of refactoring and their real-world applicability, including better tool support.

Manuscript DOI: 

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