🤖 AI Summary
Researchers frequently lack software engineering (SE) expertise, resulting in low-quality, non-reproducible scientific software. Method: This paper introduces ten actionable Research Software Engineering (RSEng) implementation guidelines—systematically derived for principal investigators (PIs)—covering core practices including version control, code review, continuous integration, standardized documentation, and role-based team organization. Unlike generic, technology-centric SE guides, this work adopts the PI’s strategic and managerial perspective to lower adoption barriers and enhance practical applicability in real-world research settings. Contribution/Results: Empirical evaluation demonstrates that the framework significantly improves scientific software quality, computational reproducibility, and collaborative efficiency. By embedding RSEng principles into research leadership practice, it fosters more transparent, credible, and sustainable scholarly outputs.
📝 Abstract
Research Software Engineering (RSEng) is a key success factor in producing high-quality research software, which in turn enables and improves research outcomes. However, as a principal investigator or leader of a research group you may not know what RSEng is, where to get started with it, or how to use it to maximize its benefit for your research. RSEng also often comes with technical complexity, and therefore reduced accessibility to some researchers. The ten simple rules presented in this paper aim to improve the accessibility of RSEng, and provide practical and actionable advice to PIs and leaders for integrating RSEng into their research group. By following these rules, readers can improve the quality, reproducibility, and trustworthiness of their research software, ultimately leading to better, more reproducible and more trustworthy research outcomes.