A Research Software Engineering Workflow for Computational Science and Engineering

TL;DR

This paper presents a practical research software engineering workflow tailored for university CSE groups, enhancing reproducibility, reusability, and quality of scientific software with minimal overhead.

Contribution

It introduces an adapted software engineering workflow for CSE that improves research software quality and reproducibility in university settings.

Findings

Workflow improves reproducibility of research results.

Minimal overhead ensures adoption by university research groups.

Enhanced linking of software, data, and publications facilitates research continuity.

Abstract

University research groups in Computational Science and Engineering (CSE) generally lack dedicated funding and personnel for Research Software Engineering (RSE), which, combined with the pressure to maximize the number of scientific publications, shifts the focus away from sustainable research software development and reproducible results. The neglect of RSE in CSE at University research groups negatively impacts the scientific output: research data - including research software - related to a CSE publication cannot be found, reproduced, or re-used, different ideas are not combined easily into new ideas, and published methods must very often be re-implemented to be investigated further. This slows down CSE research significantly, resulting in considerable losses in time and, consequentially, public funding. We propose a RSE workflow for Computational Science and Engineering (CSE) that addresses these challenges, that improves the quality of research output in CSE. Our workflow applies established software engineering practices adapted for CSE: software testing, result visualization, and periodical cross-linking of software with reports/publications and data, timed by milestones in the scientific publication process. The workflow introduces minimal work overhead, crucial for university research groups, and delivers modular and tested software linked to publications whose results can easily be reproduced. We define research software quality from a perspective of a pragmatic researcher: the ability to quickly find the publication, data, and software related to a published research idea, quickly reproduce results, understand or re-use a CSE method, and finally extend the method with new research ideas.