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

Edward R. Ivimey-Cook* (Corresponding author), 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* (Corresponding author)

*Corresponding author for this work

Research output: Contribution to journal/periodicalArticleScientificpeer-review

2 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1347-1356
Number of pages10
JournalJournal of Evolutionary Biology
Volume36
Issue number10
DOIs
Publication statusPublished - Oct 2023

Keywords

  • coding errors
  • open science
  • reliability
  • reproducibility
  • research process
  • software development
  • transparency

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