Knowledge Transfer in Modern Code Review

Caulo, Maria; Lin, Bin; Bavota, Gabriele; Scanniello, Giuseppe; Lanza, Michele

doi:10.1145/3387904.3389270

Cited by 18 publications

(6 citation statements)

References 14 publications

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“…It is explained by the authors by possible fallacies in the experiment design and threats to validity regarding the measures employed to quantify the knowledge transfer impact. However, in the light of our study, it is noteworthy that Caulo et al [41] investigated TA reviews, whereas we found that participants, with regard to the knowledge transfer, value more the OTS technique.…”

Section: Introductioncontrasting

confidence: 48%

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Code review effectiveness: an empirical study on selected factors influence

Jureczko¹,

Kajda²,

Górecki³

2020

IET softw.

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Code review is a widely adopted means of improving software quality. There are numerous techniques of reviewing including tool‐assisted and over‐the‐shoulder. Both require significant effort to perform. However, the impact the over‐the‐shoulder has on review effectiveness remains unexplored. The authors goal was to compare the techniques and the effect of review size to analyse how that affects the effectiveness. They performed three experiments within one company. Changes provided by developers were reviewed twice by different reviewers, each time using a different technique. Afterwards, participants rated in a questionnaire the influence of each technique to the knowledge transfer. They observed that the number of accepted comments reported with the tool‐assisted technique is approximately twice as big. Also, they noticed a relationship between comments density and the review size: the correlations vary from − 0.42 to − 0.33. The knowledge transfer was typically evaluated as it supports knowledge sharing to a limited extent for the tool‐assisted technique but as it is good at supporting knowledge sharing for the over‐the‐shoulder technique. The results did not give a simple answer whether one technique outperforms the other. The tool‐assisted technique results in more comments. However, the teams evaluated the over‐the‐shoulder technique as better supporting knowledge transfer.

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Section: Introductioncontrasting

confidence: 48%

“…The code review effect on knowledge transfer was also investigated by Caulo et al [41] in an analysis conducted on 32,062 peer‐reviewed pull requests made across 4981 repositories by 728 developers. Despite its size, it did not capture the positive impact code review may have on knowledge transfer.…”

Section: Introductionmentioning

confidence: 99%

Code review effectiveness: an empirical study on selected factors influence

Jureczko¹,

Kajda²,

Górecki³

2020

IET softw.

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“…They then evaluated whether, as more of their pull requests were examined, the developer's contributions to open-source projects got better over time. They failed to uncover proof, nonetheless, that the code review procedure improved the caliber of developers' contributions [25]. However, Jureczko et al noted that Caulo et al studied toolassisted reviews while Jureczko et al's tests showed that over-the-shoulder reviews have a considerably bigger influence on knowledge transfer [14] and that tool-assisted reviews do enhance knowledge transmission to some level.…”

Section: Transparency Of Codementioning

confidence: 99%

The Effectiveness of Code Reviews on Improving Software Quality: An Empirical Study

Silva,

Pabasara,

Sangkavi

et al. 2023

IJRTE

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This study intends to investigate how well code reviews contribute to higher software quality. A group of developers working on the study examine source code to find flaws, improve readability, and guarantee compliance with coding standards. The research on the effects of code review on defect discovery, defect prevention, and code maintainability is given together with a thorough overview of the literature on code review and software quality. This study has shown that code review is a highly efficient way to raise the caliber of software. According to the study of several studies and trials, code review significantly reduces flaws and improves code maintainability. Code review helps to increase client satisfaction by making sure the product satisfies their needs. The goal of this study is to highlight the value of code review as a quality assurance technique in software development workflows. The study's findings provide useful information for software development teams by emphasizing the advantages of code review for raising software quality and customer satisfaction. The results of this study can assist software development teams in incorporating code review into their workflows as a normal procedure, which would improve software quality and cut down on mistakes. In conclusion, this study shows that code review is a highly efficient way to raise the caliber of software. In terms of fault detection and prevention, code maintainability, and customer satisfaction, the study underlines the benefits of code review. This study can influence software development teams to make code review a common practice by highlighting its advantages, which would increase product quality and client satisfaction.

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“…Since its origins in the 1970s, when a formal process with strict guidelines was proposed by Fagan [1976], it is widely discussed in the literature. We found studies about the impact on software quality [McIntosh et al, 2016], security [McGraw, 2008;Edmundson et al, 2013], and knowledge transfer [Caulo et al, 2020]. Sadowski et al [2018] presented an exploratory investigation of code review practices at Google.…”

Section: Code Reviewmentioning

confidence: 99%

RAID: Tool Support for Refactoring-Aware Code Reviews

Brito

Valente

2021

2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC)

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Agradeço aos meus familiares, amigos e professores! A presença de vocês foi indispensável para a realização desse sonho. Agradeço em especial:A Deus, por permitir a conclusão desta etapa.Aos meus familiares, pelo incentivo durante este curso de mestrado. Especialmente, aos meus pais Bernadete e José, e à minha irmã Aline, por todo o carinho, apoio e conselhos recebidos.Aos meus amigos, pela amizade, suporte e por todos os momentos incríveis que passamos juntos. Em especial aos meus amigos do Aserg, pela parceria, amizade e aprendizado.Aos meus companheiros de trabalho da Studio Sol, pelo companheirismo e contribuição no meu crescimento profissional e pessoal.Ao meu orientador, Prof. Marco Tulio Valente, pela paciência, confiança e todos os ensinamentos passados durante esse período. Aos meus professores, pelo incentivo e conhecimento compartilhado durante o mestrado, graduação e ensino básico.Aos membros da banca, Prof. Ingrid Nunes e Prof. André Hora, pela disponibilidade em participar deste trabalho.Ao DCC/UFMG, FAPEMIG e CNPq, pelo suporte financeiro e acadêmico.vi "Great things are done by a series of small things brought together."(Vincent Van Gogh) vii ResumoRevisão do código é uma importante prática no desenvolvimento de software moderno. Além de detectar falhas, revisão de código contribui para a qualidade do código e transferência de conhecimento. No entanto, revisão do código leva tempo e exige uma análise detalhada e demorada de diffs textuais. Particularmente, detectar refatorações durante as revisões não é uma tarefa trivial, uma vez que as refatorações não são representadas em diffs. Nesta dissertação, nós inicialmente estendemos RefDiff -uma ferramenta de detecção de refatoração multilinguagem -para identificar refatorações na linguagem de programação Go. Nossa extensão-chamada RefDiff4Go-detecta 13 tipos de refatoração e obteve uma precisão de 92% e um recall de 80% em uma avaliação com seis projetos de código aberto populares. Em seguida, como nossa principal contribuição, nós apresentamos RAID: uma ferramenta de diff inteligente que identifica atividades de refatoração e instrumenta os diffs textuais-particularmente, os diffs fornecidos pelo GitHub-com informações de atividades de refatoração. Nosso objetivo é aliviar o esforço cognitivo associado a revisões de código, detectando automaticamente as operações de refatoração incluídas nas solicitações de pull requests. Além de propor uma arquitetura para o RAID, implementamos um plug-in para o navegador Chrome que suporta nossa solução. Também avaliamos RAID em um experimento de campo por três meses, quando oito desenvolvedores profissionais usaram nossa ferramenta em quatro projetos Go. Concluímos que RAID reduz o esforço cognitivo necessário para detectar e revisar atividades de refatoração em diffs textuais. Particularmente, RAID também reduz o número de linhas necessárias para revisar tais operações. Por exemplo, o número médio de linhas a serem revisadas diminuiu de 14,5 para 2 linhas no caso de refatorações envolvendo movimentação e de 113 p...

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Knowledge Transfer in Modern Code Review

Cited by 18 publications

References 14 publications

Code review effectiveness: an empirical study on selected factors influence

Code review effectiveness: an empirical study on selected factors influence

The Effectiveness of Code Reviews on Improving Software Quality: An Empirical Study

RAID: Tool Support for Refactoring-Aware Code Reviews

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