File-based localization of numerical perturbations in data analysis pipelines

Author:

Salari Ali1ORCID,Kiar Gregory23ORCID,Lewis Lindsay2,Evans Alan C23,Glatard Tristan1ORCID

Affiliation:

1. Department of Computer Science and Software Engineering, Concordia University, Montreal, QC, Canada

2. Department of Biomedical Engineering, McGill University, Montreal, QC, Canada

3. Montreal Neurological Institute, McGill University, Montreal, QC, Canada

Abstract

Abstract Background Data analysis pipelines are known to be affected by computational conditions, presumably owing to the creation and propagation of numerical errors. While this process could play a major role in the current reproducibility crisis, the precise causes of such instabilities and the path along which they propagate in pipelines are unclear. Method We present Spot, a tool to identify which processes in a pipeline create numerical differences when executed in different computational conditions. Spot leverages system-call interception through ReproZip to reconstruct and compare provenance graphs without pipeline instrumentation. Results By applying Spot to the structural pre-processing pipelines of the Human Connectome Project, we found that linear and non-linear registration are the cause of most numerical instabilities in these pipelines, which confirms previous findings.

Funder

Taylor Family Institute for Innovative Psychiatric Research, Washington University School of Medicine in St. Louis

Publisher

Oxford University Press (OUP)

Subject

Computer Science Applications,Health Informatics

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