Research on mining software repositories to facilitate refactoring

Author:

Nyamawe Ally S.12ORCID

Affiliation:

1. Department of Computer Science and Engineering The University of Dodoma Dodoma Tanzania

2. AI4D Africa's Anglophone Multidisciplinary Research Lab The University of Dodoma Dodoma Tanzania

Abstract

AbstractSoftware refactoring focuses on improving software quality by applying changes to the internal structure that do not alter the observable behavior. Determining which refactorings should be applied and presented to developers the most relevant and optimal refactorings is often challenging. Existing literature suggests that one of the potential sources to identify and recommend required refactorings is the past software development and evolution histories which are often archived in software repositories. In this article, we review a selection of existing literature that has attempted to propose approaches that facilitate refactoring by exploiting information mined from software repositories. Based on the reviewed papers, existing works leverage software history mining to support analysis of code smells, refactoring, and guiding software changes. First, past history information is used to detect design flaws in source code commonly referred to as code smells. Moreover, other studies analyze the evolution of code smells to establish how and when they are introduced into the code base and get resolved. Second, software repositories mining provides useful insights that can be used in predicting the need for refactoring and what specific refactoring operations are required. In addition, past history can be used in detecting and analyzing previously applied refactorings to establish software change facts, for instance, how developers refactor code and the motivation behind it. Finally, change patterns are used to predict further changes that might be required and recommend a set of files for change during a given modification task. The paper further suggests other exciting possibilities that can be pursued in the future in this research direction.This article is categorized under: Algorithmic Development > Text Mining Application Areas > Data Mining Software Tools

Publisher

Wiley

Subject

General Computer Science

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Extending Refactoring Detection to Kotlin: A Dataset and Comparative Study;2024 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER);2024-03-12

2. An Empirical Evaluation of Design Smells and Code Smells Over Multiple Versions of Software Evolution;Lecture Notes in Networks and Systems;2024

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