Rebasing in Code Review Considered Harmful: A Large-Scale Empirical Investigation

Paixao, Matheus; Maia, Paulo Henrique M.

doi:10.1109/scam.2019.00014

Cited by 14 publications

(13 citation statements)

References 28 publications

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“…While we extract the number of introduced violations in the initial and the final patch, Panichella et al compare the absolute number of violations presented in the files affected by the initial and the final patch. They are likely affected by rebasing [17].…”

Section: Discussionmentioning

confidence: 99%

“…Only merged reviews with multiple patches are of interest to us because the initially submitted patch was revised based on reviewers' comments, and the patch was finally accepted and merged into the codebase. The last two rows show how many reviews a rebasing occured, i.e., a new revision of the patch under review is relative to a different commit than the previous revision of the patch, and how many reviews tampering occurs, i.e., when external commits due to rebasing modify the same files involved in the code review [17].…”

Section: B the Crop Data Setmentioning

confidence: 99%

“…Rebasing a patch is necessary if the branch it is relative to has progressed in the development, so that the patch is relative to the current state of the branch. Paixao et al [17] demonstrate that empirical studies which do not account for rebasing may report skewed, biased and inaccurate observations, as on average 34% of all reviews are affected by modifications in the reviewed files due to rebasing. Since Panichella et al do not take rebasing into account, their observations and conclusions may be affected.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Does code review really remove coding convention violations?

Han

Ragkhitwetsagul

Krinke

et al. 2020

2020 IEEE 20th International Working Conference on Source Code Analysis and Manipulation (SCAM)

Self Cite

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Many software developers perceive technical debt as the biggest problems in their projects. They also perceive code reviews as the most important process to increase code quality. As inconsistent coding style is one source of technical debt, it is no surprise that coding convention violations can lead to patch rejection during code review. However, as most research has focused on developer's perception, it is not clear whether code reviews actually prevent the introduction of coding convention violations and the corresponding technical debt.Therefore, we investigated how coding convention violations are introduced, addressed, and removed during code review by developers. To do this, we analysed 16,442 code review requests from four projects of the Eclipse community for the introduction of convention violations. Our result shows that convention violations accumulate as code size increases despite changes being reviewed. We also manually investigated 1,268 code review requests in which convention violations disappear and observed that only a minority of them have been removed because a convention violation has been flagged in a review comment. The investigation results also highlight that one can speed up the code review process by adopting tools for code convention violation detection.

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Section: Discussionmentioning

confidence: 99%

Section: B the Crop Data Setmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Does code review really remove coding convention violations?

Han

Ragkhitwetsagul

Krinke

et al. 2020

2020 IEEE 20th International Working Conference on Source Code Analysis and Manipulation (SCAM)

Self Cite

View full text Add to dashboard Cite

show abstract

“…Paixao and Maia [16] study how rebasing is used in code reviews. In particular, they study what the side effects of rebasing are during the code review process.…”

Section: Previous Studiesmentioning

confidence: 99%

Escaping the Time Pit: Pitfalls and Guidelines for Using Time-Based Git Data

Flint¹,

Chauhan²,

Dyer³

2021

Preprint

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Many software engineering research papers rely on time-based data (e.g., commit timestamps, issue report creation/update/close dates, release dates). Like most real-world data however, time-based data is often dirty. To date, there are no studies that quantify how frequently such data is used by the software engineering research community, or investigate sources of and quantify how often such data is dirty. Depending on the research task and method used, including such dirty data could affect the research results. This paper presents the first survey of papers that utilize time-based data, published in the Mining Software Repositories (MSR) conference series. Out of the 690 technical track and data papers published in MSR 2004-2020, we saw at least 35% of papers utilized time-based data. We then used the Boa and Software Heritage infrastructures to help identify and quantify several sources of dirty commit timestamp data. Finally we provide guidelines/best practices for researchers utilizing time-based data from Git repositories.

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“…The two file sets (before and after) might not be exactly the same, due to files created and deleted during the review process. Since the before version of each revision is its parent, we guarantee that the introduced degradation symptoms between each version were solely introduced by the code changes in r i , avoiding the collateral effects of the rebase [113]. The output of this step is, for each revision in R s , the version of the files impacted before and after the revision.…”

Section: Identification Of Design Impactful Change Instancesmentioning

confidence: 99%

Unveiling Social and Technical Facets of Design Degradation in Modern Code Review

UCHOA¹

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in 2016. Anderson has worked for Research & Development (R&D) projects in software engineering and information systems for healthcare, in collaboration with institutions from Brazil and the United Kingdom (UK). His collaborative work resulted in more than 25 peer-reviewed papers. Anderson collaborates with various researchers in Brazil (more recently, UFPR, UFPE, and UFC) and UK (Newcastle University). His main research interests are software gamification, code review, software reuse, software evolution, software maintenance, and human aspects.

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Rebasing in Code Review Considered Harmful: A Large-Scale Empirical Investigation

Cited by 14 publications

References 28 publications

Does code review really remove coding convention violations?

Does code review really remove coding convention violations?

Escaping the Time Pit: Pitfalls and Guidelines for Using Time-Based Git Data

Unveiling Social and Technical Facets of Design Degradation in Modern Code Review

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