Advancing Research Software Engineering with AI: A Research Framework

Advancing Research Software Engineering with AI: A Research Framework | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Advancing Research Software Engineering with AI: A Research Framework Siamak Farshidi, Kwabena Bennin, Önder Babur, June Sallou, Ayalew Kassahun, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7178452/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract The rapid adoption of Artificial Intelligence (AI) and Generative AI (GenAI) tools is transforming the creation, maintenance, and dissemination of research software. Despite their growing prevalence, the implications of these technologies for Research Software Engineering (RSE) practices remain underexplored. This work introduces AI4RSE , an emerging research domain focused on the integration of AI into the development lifecycle of research software. To investigate current trends in AI-augmented RSE, we conducted an empirical study of more than 1,500 open-source research software repositories hosted on Zenodo. Each repository was assessed using a quadrant-based typology defined by two key dimensions: software engineering maturity and the level of AI integration. Our analysis combined static and semantic code inspection, evaluation of alignment with the FAIR Principles for Research Software (FAIR4RS), and heuristic classification of generative AI usage and MLOps adoption. Repositories are categorized into four development modes: Exploratory Coding , Vibe Coding , RSE , and AI4RSE , which reflect different levels of process rigor and AI tool integration. While many projects exhibit informal development patterns, a growing subset demonstrates mature, AI-assisted workflows. This landscape reveals key challenges, such as reproducibility risks and licensing ambiguity, while also highlighting emerging opportunities, including AI-assisted testing and intelligent documentation generation. The findings support a research agenda for AI4RSE, outlining benchmarks, guidelines, and community standards to promote responsible, reproducible, and scalable adoption of AI in scientific software development. AI for Research Software Engineering (AI4RSE) Research Software Engineering AI for Software Engineering Generative AI Software Repository Mining Research Software Maturity Assessment Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 17 Nov, 2025 Reviews received at journal 07 Oct, 2025 Reviews received at journal 06 Oct, 2025 Reviews received at journal 29 Sep, 2025 Reviews received at journal 30 Aug, 2025 Reviewers agreed at journal 07 Aug, 2025 Reviewers agreed at journal 07 Aug, 2025 Reviewers agreed at journal 07 Aug, 2025 Reviewers agreed at journal 05 Aug, 2025 Reviewers invited by journal 05 Aug, 2025 Editor assigned by journal 23 Jul, 2025 Submission checks completed at journal 23 Jul, 2025 First submitted to journal 21 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7178452","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":495941578,"identity":"5842bc04-4ecb-4121-b267-30f51d7f6ffe","order_by":0,"name":"Siamak 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