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

1. Front Neuroinform. 2018 Jan 4;11:69. doi: 10.3389/fninf.2017.00069. eCollection
2017.

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

Benureau FCY(1)(2)(3), Rougier NP(1)(2)(3).

Author information:
(1)INRIA Bordeaux Sud-Ouest, Talence, France.
(2)Institut des Maladies Neurodégénératives, Université de Bordeaux, Centre
National de la Recherche Scientifique UMR 5293, Bordeaux, France.
(3)LaBRI, Université de Bordeaux, Bordeaux INP, Centre National de la Recherche
Scientifique UMR 5800, Talence, France.

Scientific code is different from production software. Scientific code, by
producing results that are then analyzed and interpreted, participates in the
elaboration of scientific conclusions. 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. The
code should be executable (re-runnable) and produce the same result more than
once (repeatable); it should allow an investigator to reobtain the published
results (reproducible) while being easy to use, understand and modify (reusable),
and it should act as an available reference for any ambiguity in the algorithmic
descriptions of the article (replicable).

DOI: 10.3389/fninf.2017.00069
PMCID: PMC5758530
PMID: 29354046

Auteurs Bordeaux Neurocampus