A core tenet of science is the ability to independently verify research results. When computations are involved, verifiability implies reproducibility: one should be able to re-run the computations to ensure they get the same results, at which point they may want to start experimenting with variants of the computational methods, feed it different data sets, and so on. This is the motivation behind our work on Guix: we want to empower scientists by providing a tool in support of reproducible computations and experimentation.
This article is a guide to using Guix for reproducible research work: producing research articles with enough information so that anyone, anytime can re-run the computational experiments it describes. Before showing how to get this done with Guix, let’s look at existing practices and see where they fall short.
Ludovic Courtès, Marek Felšöci, Konrad Hinsen, Philippe Swartvagher — June 23, 2023