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

2017/08/31 by Fabien Benureau, Nicolas Rougier · 1 citation
Computer Science · #cs.GL #cs.CY

paper · pdf · doi:10.3389/fninf.2017.00069

Frontiers in Neuroinformatics, Frontiers, In press

arxiv created 2018/06/18 · arxiv updated 2019/04/25

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.

Cited by

• Ergodicity Library: A Python Toolkit for Stochastic-Process Simulation, Time-Average Diagnostics, and Agent-Based Experiments

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