research-article

Code Review is just reviewing code? A qualitative study with practitioners in industry

Authors:

Atacílio Cunha,

Bruno GadelhaAuthors Info & Claims

SBES '21: Proceedings of the XXXV Brazilian Symposium on Software Engineering

Pages 269 - 274

https://doi.org/10.1145/3474624.3477063

Published: 05 October 2021 Publication History

Abstract

Code review is essentially the process of assessing code made by a developer from the perspective of others. Considering the Modern Code Review (MCR) activities within the industry, many opportunities can be evaluated with the practitioners that adopt MCR within everyday software development. Based on that, we evaluated the perspective of software practitioners on code review by applying a survey to understand more about the aspects of MCR in their software development routine. Our qualitative results show that MCR activities are not only about reviewing code but also with knowledge sharing applied at team/project level or between different levels of seniority. We also found other important aspects such as identification of Cognitive Empathy and Career Development related to the MCR process. This research contributes to increase perspective that can be obtained with MCR process applied in the software development industry.

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Cited By

Oliveira DSantos Rde Oliveira BMonperrus MCastor FMadeiral F(2025)Understanding Code Understandability Improvements in Code ReviewsIEEE Transactions on Software Engineering10.1109/TSE.2024.345378351:1(14-37)Online publication date: 1-Jan-2025
https://dl.acm.org/doi/10.1109/TSE.2024.3453783
Kartal YAkdeniz EÖzkan K(2024)Automating modern code review processes with code similarity measurementInformation and Software Technology10.1016/j.infsof.2024.107490173(107490)Online publication date: Sep-2024
https://doi.org/10.1016/j.infsof.2024.107490
Lee CHicks C(2024)Understanding and effectively mitigating code review anxietyEmpirical Software Engineering10.1007/s10664-024-10550-929:6Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1007/s10664-024-10550-9
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SBES '21: Proceedings of the XXXV Brazilian Symposium on Software Engineering

September 2021

473 pages

ISBN:9781450390613

DOI:10.1145/3474624

Copyright © 2021 ACM.

© 2021 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 October 2021

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SBES '21

SBES '21: Brazilian Symposium on Software Engineering

September 27 - October 1, 2021

Joinville, Brazil

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Cited By

Oliveira DSantos Rde Oliveira BMonperrus MCastor FMadeiral F(2025)Understanding Code Understandability Improvements in Code ReviewsIEEE Transactions on Software Engineering10.1109/TSE.2024.345378351:1(14-37)Online publication date: 1-Jan-2025
https://dl.acm.org/doi/10.1109/TSE.2024.3453783
Kartal YAkdeniz EÖzkan K(2024)Automating modern code review processes with code similarity measurementInformation and Software Technology10.1016/j.infsof.2024.107490173(107490)Online publication date: Sep-2024
https://doi.org/10.1016/j.infsof.2024.107490
Lee CHicks C(2024)Understanding and effectively mitigating code review anxietyEmpirical Software Engineering10.1007/s10664-024-10550-929:6Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1007/s10664-024-10550-9
Dorner MMendez DWnuk KZabardast ECzerwonka J(2024)The upper bound of information diffusion in code reviewEmpirical Software Engineering10.1007/s10664-024-10442-y30:1Online publication date: 17-Oct-2024
https://dl.acm.org/doi/10.1007/s10664-024-10442-y
Badampudi DUnterkalmsteiner MBritto R(2023)Modern Code Reviews—Survey of Literature and PracticeACM Transactions on Software Engineering and Methodology10.1145/358500432:4(1-61)Online publication date: 26-May-2023
https://dl.acm.org/doi/10.1145/3585004
Kudrjavets GRastogi A(2023)Does code review speed matter for practitioners?Empirical Software Engineering10.1007/s10664-023-10401-z29:1Online publication date: 22-Nov-2023
https://dl.acm.org/doi/10.1007/s10664-023-10401-z
Panighrahi RKuanar SKumar L(2022)Cross-Project Software Refactoring Prediction Using Optimized Deep Learning Neural Network With the Aid of Attribute SelectionInternational Journal of Open Source Software and Processes10.4018/IJOSSP.30075613:1(1-31)Online publication date: 20-May-2022
https://dl.acm.org/doi/10.4018/IJOSSP.300756
Rahman SKoana UNayebi M(2022)Example Driven Code Review ExplanationProceedings of the 16th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement10.1145/3544902.3546639(307-312)Online publication date: 19-Sep-2022
https://dl.acm.org/doi/10.1145/3544902.3546639

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