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How reproducible should research software be?

Authors: Harrison, Sam; Dasgupta, Abhishek; Waldman, Simon; Henderson, Alex; Lovell, Christopher;

How reproducible should research software be?

Abstract

In this article, we attempt to answer the question of how reproducible research software should be by defining four levels of reproducibility, suggesting criteria to help you decide which level your research software should be at, and recommending practices to reach these levels of reproducibility. The article is the result of a discussion session at the Software Sustainability Institute Fellows Online Selection Day 2021.

{"references": ["Wilson et al (2017). Good enough practices in scientific computing. doi: 10.1371/journal.pcbi.1005510", "Lee et al (2021). Barely sufficient practices in scientific computing. doi: 10.1016/j.patter.2021.100206", "McArthur (2019). Repeatability, Reproducibility, and Replicability: Tackling the 3R challenge in biointerface science and engineering. doi: 10.1116/1.5093621"]}

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Keywords

software sustainability, research software, reproducibility

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selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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