  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.
