Characterizing the Usefulness of Code Review Comments in Scientific Software for Software Quality and Scientific Rigor

2026-04-26

AI Summary

This study addresses the lack of systematic research on the usefulness of code review comments in scientific open-source software, a gap that hinders both software quality and research reproducibility. Drawing on GitHub data and employing textual analysis alongside statistical comparisons, this work provides the first systematic characterization of useful review comments in scientific software and examines how they differ from or align with those in general-purpose software. The findings reveal that 6%–33% of comments are unhelpful, with negative or subjective language generally diminishing perceived usefulness. Emoji usage shows only a weak association with comment utility: negative emojis slightly increase the likelihood of a comment being deemed unhelpful, while the effect of positive emojis is more nuanced. These results offer empirical foundations for improving code review practices in scientific software development.

Technology Category

• Natural Language Processing: Code Generation / Program Synthesis from Natural Language
• Application Domains: Humanities & Computational Social Science
• Reasoning under Uncertainty: Causality

Application Category

• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets

Abstract

Context: Innovation thrives on scientific software, with useful code review feedback enhancing its correctness and impact. However, unlike general-purpose commercial and open-source software, the usefulness of code review feedback (CR comment) in scientific software remains largely unstudied. Objective: This paper aims to characterize the usefulness of CR comment in scientific opens ource software (Sci-OSS), leveraging existing research on useful CR comment. Method: To achieve this objective, we mine successful Sci-OSS from GitHub, analyze their CR comments with usefulness related features, and compare the findings from prior research on general-purpose commercial and open-source CR comments. Results: The investigation on the usefulness of CR comments in SciOSS confirms many characteristics that prior research identified in general-purpose software. For example, subjective or negative CR comments remain not useful for the Sci-OSS. We also find CR comments which receive negative emoji reactions have a very small correlation with not useful comments, whereas the positive emojis show mixed correlations. Importantly, 6-33% CR comments in Sci-OSS are not useful in our mined repositories. Conclusions: Our investigation into Sci-OSS extends findings from CR comments' usefulness research on general-purpose software, benefiting developers, scientists, and researchers in the Sci-OSS community.

Problem

• code review comments
• scientific software
• software quality
• scientific rigor
• usefulness

Innovation

• code review usefulness
• scientific software
• open-source software
• emoji reactions
• software quality