Reproducibility is a process, not an achievement: The replicability of IR reproducibility experiments

Abstract

This paper espouses a view of reproducibility in the computational sciences as a process and not just a point-in-time “achievement”. As a concrete case study, we revisit the Open-Source IR Reproducibility Challenge from 2015 and attempt to replicate those experiments: four years later, are those computational artifacts still functional? Perhaps not surprisingly, we are not able to replicate most of the retrieval runs encapsulated by those artifacts in a modern computational environment. We outline the various idiosyncratic reasons why, distilled into a series of “lessons learned” to help form an emerging set of best practices for the long-term sustainability of reproducibility efforts.