Do explicit review strategies improve code review performance? Towards understanding the role of cognitive load

Empirical Software Engineering(2022)

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摘要
Code review is an important process in software engineering – yet, a very expensive one. Therefore, understanding code review and how to improve reviewers’ performance is paramount. In the study presented in this work, we test whether providing developers with explicit reviewing strategies improves their review effectiveness and efficiency. Moreover, we verify if review guidance lowers developers’ cognitive load. We employ an experimental design where professional developers have to perform three code review tasks. Participants are assigned to one of three treatments: ad hoc reviewing, checklist, and guided checklist. The guided checklist was developed to provide an explicit reviewing strategy to developers. While the checklist is a simple form of signaling (a method to reduce cognitive load), the guided checklist incorporates further methods to lower cognitive demands of the task such as segmenting and weeding. The majority of the participants are novice reviewers with low or no code review experience. Our results indicate that the guided checklist is a more effective aid for a simple review,while the checklist supports reviewers’ efficiency and effectiveness in a complex task. However, we did not identify a strong relationship between the guidance provided and code review performance. The checklist has the potential to lower developers’ cognitive load, but higher cognitive load led to better performance possibly due to the generally low effectiveness and efficiency of the study participants. Data and materials: https://doi.org/10.5281/zenodo.5653341 . Registered report: https://doi.org/10.17605/OSF.IO/5FPTJ .
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关键词
Code review,Reviewing strategies,Checklist-based reading,Cognitive load
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