Implementing code review in the scientific workflow: Insights from ecology and evolutionary biology |
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| Authors: | Edward R Ivimey-Cook Joel L Pick Kevin R Bairos-Novak Antica Culina Elliot Gould Matthew Grainger Benjamin M Marshall David Moreau Matthieu Paquet Raphaël Royauté Alfredo Sánchez-Tójar Inês Silva Saras M Windecker |
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| Institution: | 1. School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, UK;2. Institute of Ecology and Evolution, University of Edinburgh, Edinburgh, UK;3. Australian Research Council Centre of Excellence for Coral Reef Studies & College of Science and Engineering, James Cook University, Townsville, Queensland, Australia;4. Rudjer Boskovic Institute, Zagreb, Croatia;5. School of Ecosystem and Forest Sciences, University of Melbourne, Melbourne, Victoria, Australia;6. Norwegian Institute for Nature Research, Trondheim, Norway;7. Biological and Environmental Sciences, Faculty of Natural Sciences, University of Stirling, Stirling, UK;8. School of Psychology, Centre for Brain Research, University of Auckland, Auckland, New Zealand;9. Institute of Mathematics of Bordeaux, University of Bordeaux, CNRS, Bordeaux INP, Talence, France;10. Université ParisSaclay, INRAE, AgroParisTech, UMR EcoSys, Palaiseau, France;11. Department of Evolutionary Biology, Bielefeld University, Bielefeld, Germany;12. Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf e.V. (HZDR), Görlitz, Germany |
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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. |
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| Keywords: | coding errors open science reliability reproducibility research process software development transparency |
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