Implementing code review in the scientific workflow: Insights from ecology and evolutionary biology

Ivimey-Cook, Edward R., Pick, Joel L., Bairos-Novak, Kevin R., Culina, Antica, Gould, Elliot, Grainger, Matthew, Marshall, Benjamin M., Moreau, David, Paquet, Matthieu, Royauté, Raphaël, Sánchez-Tójar, Alfredo, Silva, Inês, and Windecker, Saras M. (2023) Implementing code review in the scientific workflow: Insights from ecology and evolutionary biology. Journal of Evolutionary Biology, 36 (10). pp. 1347-1356.

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Abstract

Code review increases reliability and improves reproducibility of research. As such, code review is an inevitable step in software development and is common in fields such as computer science. However, despite its importance, code review is noticeably lacking in ecology and evolutionary biology. This is problematic as it facilitates the propagation of coding errors and a reduction in reproducibility and reliability of published results. To address this, we provide a detailed commentary on how to effectively review code, how to set up your project to enable this form of review and detail its possible implementation at several stages throughout the research process. This guide serves as a primer for code review, and adoption of the principles and advice here will go a long way in promoting more open, reliable, and transparent ecology and evolutionary biology.

Item ID: 80842
Item Type: Article (Research - C1)
ISSN: 1420-9101
Keywords: coding errors, open science, reliability, reproducibility, research process, software development, transparency
Copyright Information: © 2023 The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Date Deposited: 20 Feb 2024 02:25
FoR Codes: 31 BIOLOGICAL SCIENCES > 3103 Ecology > 310399 Ecology not elsewhere classified @ 50%
31 BIOLOGICAL SCIENCES > 3104 Evolutionary biology > 310499 Evolutionary biology not elsewhere classified @ 50%
SEO Codes: 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280102 Expanding knowledge in the biological sciences @ 100%
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