Re-run, Repeat, Reproduce, Reuse, Replicate: Transforming Code into Scientific Contributions

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.

Frontiers in Neuroinformatics, Frontiers, In press

References in corpus (4)

• Can parametric statistical methods be trusted for fMRI based group studies?
• Sustainable computational science: the ReScience initiative
• Journal of Open Source Software (JOSS): design and first-year review
• Reproducible and replicable CFD: it's harder than you think

Cited by in corpus (9)

• Packaging research artefacts with RO-Crate
• Perils of Zero-Interaction Security in the Internet of Things
• Computational Experiment Design for Operations Model Simulation
• Best Practices for Notification Studies for Security and Privacy Issues on the Internet
• Good modelling software practices
• On the reproducibility of discrete-event simulation studies in health research: an empirical study using open models
• Formal Definition and Implementation of Reproducibility Tenets for Computational Workflows
• Computational models of astrocyte function at glutamatergic synapses
• Zero-Interaction Security -- Towards Sound Experimental Validation