Assessing the Refactoring of Brain Methods

Author:

Vidal Santiago1ORCID,berra Iñaki2,Zulliani Santiago2,Marcos Claudia3,Pace J. Andrés Díaz4

Affiliation:

1. ISISTAN-CONICET, Argentina

2. UNICEN University, Tandil, Argentina

3. ISISTAN-CIC, Argentina, Buenos Aires, Argentina

4. ISISTAN-CONICET, Argentina, Buenos Aires, Argentina

Abstract

Code smells are a popular mechanism for identifying structural design problems in software systems. Several tools have emerged to support the detection of code smells and propose some refactorings. However, existing tools do not guarantee that a smell will be automatically fixed by means of refactorings. This article presents Bandago, an automated approach to fix a specific type of code smell called Brain Method . A Brain Method centralizes the intelligence of a class and manifests itself as a long and complex method that is difficult to understand and maintain by developers. For each Brain Method , Bandago recommends several refactoring solutions to remove the smell using a search strategy based on simulated annealing. Our approach has been evaluated with several open-source Java applications, and the results show that Bandago can automatically fix more than 60% of Brain Methods . Furthermore, we conducted a survey with 35 industrial developers that showed evidence about the usefulness of the refactorings proposed by Bandago. Also, we compared the performance of the Bandago against that of a third-party refactoring tool.

Publisher

Association for Computing Machinery (ACM)

Subject

Software

Cited by 8 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. Practitioners' Expectations on Code Smell Detection;2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC);2024-07-02

2. Behind the Intent of Extract Method Refactoring: A Systematic Literature Review;IEEE Transactions on Software Engineering;2024-04

3. Software defects detection and classification by using data mining techniques in Integrated Development Environment (IDE): Survey;INTERNATIONAL CONFERENCE ON SCIENTIFIC RESEARCH & INNOVATION (ICSRI 2022);2023

4. Empirical Study on Method-level Refactoring Using Machine Learning;Lecture Notes in Networks and Systems;2022-09-27

5. Design and Implementation of a Web-Based Application for Code Smells Repository;Tehnički glasnik;2021-09-14

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