TL;DR
This paper emphasizes the importance of scientific code possessing five key characteristics—re-runnable, repeatable, reproducible, reusable, and replicable—to ensure it effectively supports scientific hypothesis evaluation.
Contribution
It clarifies the specific constraints scientific code must meet and advocates for transforming code into reliable scientific contributions.
Findings
Identifies five essential characteristics for scientific code
Highlights overlooked constraints in scientific coding practices
Proposes a framework for improving scientific code reliability
Abstract
Scientific code is not production software. Scientific code participates in the evaluation of a scientific hypothesis. This imposes specific constraints on the code that are often overlooked in practice. We articulate, with a small example, five characteristics that a scientific code in computational science should possess: re-runnable, repeatable, reproducible, reusable and replicable.
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