research-article

Behind the Intents: An In-depth Empirical Study on Software Refactoring in Modern Code Review

Authors:

Matheus Paixão,

Anderson Uchôa,

Ana Carla Bibiano,

Daniel Oliveira,

Alessandro Garcia,

Emilio ArvonioAuthors Info & Claims

MSR '20: Proceedings of the 17th International Conference on Mining Software Repositories

Pages 125 - 136

https://doi.org/10.1145/3379597.3387475

Published: 18 September 2020 Publication History

Abstract

Code refactorings are of pivotal importance in modern code review. Developers may preserve, revisit, add or undo refactorings through changes' revisions. Their goal is to certify that the driving intent of a code change is properly achieved. Developers' intents behind refactorings may vary from pure structural improvement to facilitating feature additions and bug fixes. However, there is little understanding of the refactoring practices performed by developers during the code review process. It is also unclear whether the developers' intents influence the selection, composition, and evolution of refactorings during the review of a code change. Through mining 1,780 reviewed code changes from 6 systems pertaining to two large open-source communities, we report the first in-depth empirical study on software refactoring during code review. We inspected and classified the developers' intents behind each code change into 7 distinct categories. By analyzing data generated during the complete reviewing process, we observe: (i) how refactorings are selected, composed and evolved throughout each code change, and (ii) how developers' intents are related to these decisions. For instance, our analysis shows developers regularly apply non-trivial sequences of refactorings that crosscut multiple code elements (i.e., widely scattered in the program) to support a single feature addition. Moreover, we observed that new developers' intents commonly emerge during the code review process, influencing how developers select and compose their refactorings to achieve the new and adapted goals. Finally, we provide an enriched dataset that allows researchers to investigate the context and motivations behind refactoring operations during the code review process.

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Cited By

Krüger JLi YLossev KZhu CChechik MBerger TRubin J(2024)A Meta-Study of Software-Change IntentionsACM Computing Surveys10.1145/3661484Online publication date: 25-Apr-2024
https://doi.org/10.1145/3661484
Middleton JOre JStolee KRoychoudhury APaiva AAbreu RStorey M(2024)Barriers for Students During Code Change ComprehensionProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3639227(1-13)Online publication date: 20-May-2024
https://dl.acm.org/doi/10.1145/3597503.3639227
Guo QCao JXie XLiu SLi XChen BPeng XRoychoudhury APaiva AAbreu RStorey M(2024)Exploring the Potential of ChatGPT in Automated Code Refinement: An Empirical StudyProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3623306(1-13)Online publication date: 20-May-2024
https://dl.acm.org/doi/10.1145/3597503.3623306
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Index Terms

Behind the Intents: An In-depth Empirical Study on Software Refactoring in Modern Code Review
1. Software and its engineering
  1. Software creation and management
    1. Software post-development issues
      1. Software evolution
  2. Software notations and tools
    1. Software maintenance tools

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cover image ACM Conferences

MSR '20: Proceedings of the 17th International Conference on Mining Software Repositories

June 2020

675 pages

ISBN:9781450375177

DOI:10.1145/3379597

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 18 September 2020

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https://doi.org/10.1145/3661484
Middleton JOre JStolee KRoychoudhury APaiva AAbreu RStorey M(2024)Barriers for Students During Code Change ComprehensionProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3639227(1-13)Online publication date: 20-May-2024
https://dl.acm.org/doi/10.1145/3597503.3639227
Guo QCao JXie XLiu SLi XChen BPeng XRoychoudhury APaiva AAbreu RStorey M(2024)Exploring the Potential of ChatGPT in Automated Code Refinement: An Empirical StudyProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3623306(1-13)Online publication date: 20-May-2024
https://dl.acm.org/doi/10.1145/3597503.3623306
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