short-paper

Impact of change granularity in refactoring detection

Authors:

Shinpei HayashiAuthors Info & Claims

ICPC '22: Proceedings of the 30th IEEE/ACM International Conference on Program Comprehension

Pages 565 - 569

https://doi.org/10.1145/3524610.3528386

Published: 20 October 2022 Publication History

Abstract

Detecting refactorings in commit history is essential to improve the comprehension of code changes in code reviews and to provide valuable information for empirical studies on software evolution. Several techniques have been proposed to detect refactorings accurately at the granularity level of a single commit. However, refactorings may be performed over multiple commits because of code complexity or other real development problems, which is why attempting to detect refactorings at single-commit granularity is insufficient. We observe that some refactorings can be detected only at coarser granularity, that is, changes spread across multiple commits. Herein, this type of refactoring is referred to as coarse-grained refactoring (CGR). We compared the refactorings detected on different granularities of commits from 19 open-source repositories. The results show that CGRs are common, and their frequency increases as the granularity becomes coarser. In addition, we found that Move-related refactorings tended to be the most frequent CGRs. We also analyzed the causes of CGR and suggested that CGRs will be valuable in refactoring research.

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Cited By

Al Dallal JAbdulsalam HAlMarzouq MSelamat A(2023)Machine Learning-Based Exploration of the Impact of Move Method Refactoring on Object-Oriented Software Quality AttributesArabian Journal for Science and Engineering10.1007/s13369-023-08174-049:3(3867-3885)Online publication date: 21-Aug-2023
https://doi.org/10.1007/s13369-023-08174-0

Index Terms

Impact of change granularity in refactoring detection
1. Software and its engineering
  1. Software creation and management
    1. Software post-development issues
      1. Software evolution

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Published In

cover image ACM Conferences

ICPC '22: Proceedings of the 30th IEEE/ACM International Conference on Program Comprehension

May 2022

698 pages

ISBN:9781450392983

DOI:10.1145/3524610

Conference Chairs:
Ayushi Rastogi
University of Groningen, The Netherlands
,
Rosalia Tufano
USI Università della Svizzera italiana, Switzerland
,
General Chair:
Gabriele Bavota
USI Università della Svizzera italiana, Switzerland
,
Program Chairs:
Venera Arnaoudova
Washington State University, United States of America
,
Sonia Haiduc
Florida State University, United States of America

Copyright © 2022 ACM.

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Published: 20 October 2022

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May 16 - 17, 2022

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Cited By

Al Dallal JAbdulsalam HAlMarzouq MSelamat A(2023)Machine Learning-Based Exploration of the Impact of Move Method Refactoring on Object-Oriented Software Quality AttributesArabian Journal for Science and Engineering10.1007/s13369-023-08174-049:3(3867-3885)Online publication date: 21-Aug-2023
https://doi.org/10.1007/s13369-023-08174-0

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