Collaborations and Code Reviews

Carver, Jeffrey C.; Çağlayan, Bora; Habayeb, Mayy; Penzenstadler, Birgit; Yamashita, Aiko

doi:10.1109/ms.2015.113

Cited by 2 publications

(4 citation statements)

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“…Code reviews have been widely used in open source and industrial software projects [6,15,32,[58][59][60]. One of the main motivations for using code reviews is to improve the quality of new patches [4,13,59].…”

Section: Contemporary Code Review Processesmentioning

confidence: 99%

“…Then, we use the implementation of Pydriller to identify a set of the commits that recently modified the same lines in the files that are included in the commit of interest. 15 Finally, those recent commits that made changes to the same lines prior to the commit of interest are identified as fix-inducing commits.…”

Section: The Association Between Visible Information and An Evaluation Decisionmentioning

confidence: 99%

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Review Dynamics and Their Impact on Software Quality

Thongtanunam

Hassan

2021

IIEEE Trans. Software Eng.

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Code review is a crucial activity for ensuring the quality of software products. Unlike the traditional code review process of the past where reviewers independently examine software artifacts, contemporary code review processes allow teams to collaboratively examine and discuss proposed patches. While the visibility of reviewing activities including review discussions in a contemporary code review tends to increase developer collaboration and openness, little is known whether such visible information influences the evaluation decision of a reviewer or not (i.e., knowing others' feedback about the patch before providing ones own feedback). Therefore, in this work, we set out to investigate the review dynamics, i.e., a practice of providing a vote to accept a proposed patch, in a code review process. To do so, we first characterize the review dynamics by examining the relationship between the evaluation decision of a reviewer and the visible information about a patch under review (e.g., comments and votes that are provided by prior co-reviewers). We then investigate the association between the characterized review dynamics and the defect-proneness of a patch. Through a case study of 83,750 patches of the OpenStack and Qt projects, we observe that the amount of feedback (either votes and comments of prior reviewers) and the co-working frequency of a reviewer with the patch author are highly associated with the likelihood that the reviewer will provide a positive vote to accept a proposed patch. Furthermore, we find that the proportion of reviewers who provided a vote consistent with prior reviewers is significantly associated with the defect-proneness of a patch. However, the associations of these review dynamics are not as strong as the confounding factors (i.e., patch characteristics and overall reviewing activities). Our observations shed light on the implicit influence of the visible information about a patch under review on the evaluation decision of a reviewer. Our findings suggest that the code reviewing policies that are mindful of these practices may help teams improve code review effectiveness. Nonetheless, such review dynamics should not be too concerning in terms of software quality.

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Section: Contemporary Code Review Processesmentioning

confidence: 99%

Section: The Association Between Visible Information and An Evaluation Decisionmentioning

confidence: 99%

Review Dynamics and Their Impact on Software Quality

Thongtanunam

Hassan

2021

IIEEE Trans. Software Eng.

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“…Although MCR has addressed many shortcomings of Fagan's code inspections and is developed to improve software and code quality through extensive knowledge sharing among MCR team members [6], [8], [9], [11], [12], however, the MCR generates waiting waste due to poor knowledge sharing [5], [8], [13], [14], [15], [16], [17], [18].…”

Section: Introductionmentioning

confidence: 99%

“…For example, in MCR delay between submitting source code review request by the author to the reviewer and getting feedback from the reviewer [8], [9], [17]. It is argued that one of the reasons for waiting waste in MCR is a poor knowledge sharing [5], [8], [13], [14], [15], [16], [17], [18]. The waiting waste decreases the productivity and efficiency of the developers [2], [4], [8], [12], [16], [17], [21], [26], [32].…”

Section: Introductionmentioning

confidence: 99%

Knowledge Sharing Factors for Modern Code Review to Minimize Software Engineering Waste

Fatima¹,

Nazir²,

Chuprat³

2020

IJACSA

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Software engineering activities, for instance, Modern Code Review (MCR) produce quality software by identifying the defects from the code. It involves social coding and provides ample opportunities to share knowledge among MCR team members. However, the MCR team is confronted with the issue of waiting waste due to poor knowledge sharing among MCR team members. As a result, it delays the project delays and increases mental distress. To minimize the waiting waste, this study aims to identify knowledge sharing factors that impact knowledge sharing in MCR. The methodology employed for this study is a systematic literature review to identify knowledge sharing factors, data coding with continual comparison and memoing techniques of grounded theory to produce a unique and categorized list of factors influencing knowledge sharing. The identified factors were then assessed through expert panel for its naming, expressions, and categorization. The study finding reported 22 factors grouped into 5 broad categories i.e. Individual, Team, Social, Facility conditions, and Artifact. The study is useful for researchers to extend the research and for the MCR team to consider these factors to enhance knowledge sharing and to minimize waiting waste.

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Collaborations and Code Reviews

Cited by 2 publications

References 0 publications

Review Dynamics and Their Impact on Software Quality

Review Dynamics and Their Impact on Software Quality

Knowledge Sharing Factors for Modern Code Review to Minimize Software Engineering Waste

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