# File-based localization of numerical perturbations in data analysis pipelines

arXiv: https://arxiv.org/abs/2006.04684 · HTML: https://mlsanity.com/paper/2006.04684/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Jun 2020.

## Built on by (most cited first, 1 of 1)

- [Data Augmentation Through Monte Carlo Arithmetic Leads to More Generalizable Classification in Connectomics](https://mlsanity.com/paper/2109.09649/) (2021)

## Abstract (arXiv)

Data analysis pipelines are known to be impacted by computational conditions, presumably due 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. 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. 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.