research-article

How does refactoring affect internal quality attributes?: A multi-project study

Authors:

Alexander Chávez,

Isabella Ferreira,

Eduardo Fernandes,

Alessandro GarciaAuthors Info & Claims

SBES '17: Proceedings of the XXXI Brazilian Symposium on Software Engineering

Pages 74 - 83

https://doi.org/10.1145/3131151.3131171

Published: 20 September 2017 Publication History

Abstract

Refactoring is a technique commonly applied by developers along the software maintenance and evolution. Software refactoring is expected to improve the internal quality attributes of a software project, such as coupling and cohesion. However, there is limited understanding on to what extent developers achieve this expectation when refactoring their source code This study investigates how refactoring operations affect five well-known internal quality attributes: cohesion, coupling, complexity, inheritance, and size. For this purpose, we analyze the version history of 23 open source projects with 29,303 refactoring operations. Our analysis revealed interesting observations. First, we noticed that developers apply more than 94% of the refactoring operations to code elements with at least one critical internal quality attribute, as opposed to previous work. Second, 65% of the refactoring operations improve their related internal quality attributes and the remaining 35% operations keep the quality attributes unaffected. Third, whenever pure refactoring operations are applied (the so-called root-canal refactoring), we confirm that internal quality attributes are either frequently improved or at least not worsened. Finally, while refactoring operations often reach other specific aims, such as adding a new feature or fixing a bug, 55% of these operations surprisingly improve internal quality attributes against only 10% of quality decline.

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Cited By

Almogahed AMahdin HHyeon Gu YAl-Masni MAlzaeemi SOmar MAlawadhi AObaid Barraood SRehman Gilal AAmeen Bakather A(2025)Multi-Classification Refactoring Framework Using Hopfield Neural Network for Sustainable Software DevelopmentIEEE Access10.1109/ACCESS.2025.354208713(31785-31808)Online publication date: 2025
https://doi.org/10.1109/ACCESS.2025.3542087
Bibiano ACoutinho DUchôa AAssunção WGarcia Ade Mello RColanzi TTenório DVasconcelos AFonseca BRibeiro M(2024)Enhancing Recommendations of Composite Refactorings based on the Practice2024 IEEE International Conference on Source Code Analysis and Manipulation (SCAM)10.1109/SCAM63643.2024.00018(83-93)Online publication date: 7-Oct-2024
https://doi.org/10.1109/SCAM63643.2024.00018
Swain VPanigrahi RSahu KPadhy N(2024)Revealing MOVE METHOD: Machine Learning-driven Real-time Refactoring Identification for Enhanced Software Quality2024 International Conference on Emerging Systems and Intelligent Computing (ESIC)10.1109/ESIC60604.2024.10481609(572-578)Online publication date: 9-Feb-2024
https://doi.org/10.1109/ESIC60604.2024.10481609
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Index Terms

How does refactoring affect internal quality attributes?: A multi-project study
1. General and reference
  1. Cross-computing tools and techniques
    1. Empirical studies
    2. Measurement
2. Software and its engineering
  1. Software creation and management
    1. Software post-development issues
      1. Maintaining software
      2. Software evolution

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Published In

cover image ACM Other conferences

SBES '17: Proceedings of the XXXI Brazilian Symposium on Software Engineering

September 2017

409 pages

ISBN:9781450353267

DOI:10.1145/3131151

Program Chairs:
José Carlos Maldonado
ICMC-USP
,
Fabiano Cutigi Ferrari
UFSCar
,
Uirá Kulesza
DIMAp/UFRN
,
Tayana Uchôa Conte
UFAM

Copyright © 2017 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]

In-Cooperation

SBC: Brazilian Computer Society
CNPq: Conselho Nacional de Desenvolvimento Cientifico e Tecn
CAPES: Brazilian Higher Education Funding Council

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 September 2017

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CAPES/Procad
FAPERJ
CNPq

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SBES'17

SBES'17: 31st Brazilian Symposium on Software Engineering

September 20 - 22, 2017

CE, Fortaleza, Brazil

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SBES '17 Paper Acceptance Rate 42 of 134 submissions, 31%;

Overall Acceptance Rate 147 of 427 submissions, 34%

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Cited By

Almogahed AMahdin HHyeon Gu YAl-Masni MAlzaeemi SOmar MAlawadhi AObaid Barraood SRehman Gilal AAmeen Bakather A(2025)Multi-Classification Refactoring Framework Using Hopfield Neural Network for Sustainable Software DevelopmentIEEE Access10.1109/ACCESS.2025.354208713(31785-31808)Online publication date: 2025
https://doi.org/10.1109/ACCESS.2025.3542087
Bibiano ACoutinho DUchôa AAssunção WGarcia Ade Mello RColanzi TTenório DVasconcelos AFonseca BRibeiro M(2024)Enhancing Recommendations of Composite Refactorings based on the Practice2024 IEEE International Conference on Source Code Analysis and Manipulation (SCAM)10.1109/SCAM63643.2024.00018(83-93)Online publication date: 7-Oct-2024
https://doi.org/10.1109/SCAM63643.2024.00018
Swain VPanigrahi RSahu KPadhy N(2024)Revealing MOVE METHOD: Machine Learning-driven Real-time Refactoring Identification for Enhanced Software Quality2024 International Conference on Emerging Systems and Intelligent Computing (ESIC)10.1109/ESIC60604.2024.10481609(572-578)Online publication date: 9-Feb-2024
https://doi.org/10.1109/ESIC60604.2024.10481609
Tarwani SChug A(2024)Determination of optimum refactoring sequence for maximizing the maintainability of object-oriented systems using machine learning algorithmsInternational Journal of System Assurance Engineering and Management10.1007/s13198-024-02639-716:2(651-666)Online publication date: 7-Dec-2024
https://doi.org/10.1007/s13198-024-02639-7
Agnihotri MChug A(2024)Understanding the effect of batch refactoring on software qualityInternational Journal of System Assurance Engineering and Management10.1007/s13198-023-02247-x15:6(2328-2336)Online publication date: 7-Feb-2024
https://doi.org/10.1007/s13198-023-02247-x
Martins LPontillo VCosta HFerrucci FPalomba FMachado I(2024)Test code refactoring unveiled: where and how does it affect test code quality and effectiveness?Empirical Software Engineering10.1007/s10664-024-10577-y30:1Online publication date: 16-Nov-2024
https://doi.org/10.1007/s10664-024-10577-y
Kalhor SKeyvanpour MSalajegheh A(2024)A systematic review of refactoring opportunities by software antipattern detectionAutomated Software Engineering10.1007/s10515-024-00443-y31:2Online publication date: 15-May-2024
https://doi.org/10.1007/s10515-024-00443-y
Agnihotri MChug A(2024)Severity Factor (SF)Journal of Software: Evolution and Process10.1002/smr.259036:5Online publication date: 25-Apr-2024
https://dl.acm.org/doi/10.1002/smr.2590
Almogahed AMahdin HOmar MZakaria NAlawadhi ABarraood S(2023)Empirical Investigation of the Diverse Refactoring Effects on Software Quality: The Role of Refactoring Tools and Software Size2023 3rd International Conference on Emerging Smart Technologies and Applications (eSmarTA)10.1109/eSmarTA59349.2023.10293407(1-6)Online publication date: 10-Oct-2023
https://doi.org/10.1109/eSmarTA59349.2023.10293407
Ferreira TIvers JYackley JKessentini MOzkaya IGaaloul K(2023)Dependent or Not: Detecting and Understanding Collections of RefactoringsIEEE Transactions on Software Engineering10.1109/TSE.2023.3244123(1-15)Online publication date: 2023
https://doi.org/10.1109/TSE.2023.3244123
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