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A Research Software Engineering Workflow for Computational Science and Engineering

Authors: Schwarzmeier, Moritz; Marić, Tomislav; Tolle, Tobias; Gläser, Dennis; Lehr, Jan-Patrick; Pappagianidis, Ioannis; Lambie, Benjamin; +2 Authors

A Research Software Engineering Workflow for Computational Science and Engineering

Abstract

We present a Research Software Engineering (RSE) workflow for developing research software in Computational Science and Engineering (CSE) in university research groups. Their members have backgrounds from different scientific disciplines and often no education in RSE. Research software development lasts many years, contrary to team members leaving regularly. Combining and re-using ideas and results from others is a fundamental principle of science. In CSE research software embodies research ideas. As CSE research advances, research software should grow sustainably over the years. To increase the sustainability of research software, our workflow simplifies the investigation and integration of research ideas, ensures reproducibility and new functionality does not impair existing one. These practices speed up research and increase the quality of scientific output. Our CSE-RSE workflow is simple, effective and largely ensures the FAIR principles.The workflow uses established practices and tools, pragmatically adapted for CSE research software: version-control, secondary-data standards, continuous integration and containerization.

Versions: v1.0: held at the NFDI4Ing Conference 2022, online, 26-27 October 2022 (Session Research Software), https://nfdi4ing.de/conference v1.1: held at the deRSE23 - Conference for Research Software Engineering in Germany, Paderborn, 20-22 February 2023, https://de-rse23.sciencesconf.org/

{"references": ["https://knowledge-base.nfdi4ing.de/"]}

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Keywords

continuous integration, research software, research data management, research software engineering, software engineering

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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