Examples
Worked examples
- Is an instance
A JOSS submission undergoing open peer review on GitHub with editor-assigned reviewers.
- Is an instance
An rOpenSci review of a community R package against the rOpenSci packaging guidelines.
Counter-examples
Looks similar, but isn't
- Not an instance
An automated linter run.
- Not an instance
A reproducibility audit of a single paper's analysis.
Editorial commentary
Code review for research software is an independent check of analysis or research software code — by someone other than its author — for correctness, clarity, and reproducibility, distinct from peer review of the scientific claims the code was used to produce. Where industrial code review is typically routine and line-by-line, integrated into every change via pull requests, code review of research code is comparatively rare, inconsistent in scope, and often skipped entirely for code that never leaves a single researcher’s laptop.
Why it matters for reproducibility
Because a published scientific conclusion frequently depends on the correctness of the code that produced it, an unreviewed analysis script is a point where an error can silently propagate into a paper’s results without anyone but the original author ever having checked the logic. Code review catches this class of error — and improves documentation and reusability — in a way that reviewing only the resulting manuscript cannot, since manuscript peer review rarely re-executes the underlying code.
Models in practice
A few formal community models exist alongside informal lab-level review: rOpenSci runs peer review of R packages against defined criteria before accepting a package into its collection; pyOpenSci runs an equivalent review process for Python packages; and JOSS (Journal of Open Source Software) integrates open, public code review directly into its publication workflow, so the review itself becomes part of the public record alongside the resulting short paper. These are heavier processes than most single-study analysis code receives, and are aimed primarily at reusable software packages rather than one-off analysis scripts.
In practice
For a typical study, code review is one component of the broader reproducible research practices a team adopts, alongside deposit of the reviewed code and a data availability statement. Even a lightweight internal review — a co-author or lab colleague re-running the pipeline before submission — closes a meaningful share of the gap between unreviewed and formally reviewed code.
References
- Smith et al., ‘Journal of Open Source Software (JOSS): design and first-year review’ (PeerJ Computer Science, 2018); rOpenSci Statistical Software Peer Review Guide.
Also known as
scientific code review · software peer review
Machine-readable encodings
Use in your systems
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