I am thrilled to announce that the paper titled “A numerical variability approach to results stability tests and its application to neuroimaging” has been accepted for publication in IEEE Transactions on Computers (TC) journal.

Description

Ensuring the long-term reproducibility of data anal- yses requires results stability tests to verify that analysis results remain within acceptable variation bounds despite inevitable software updates and hardware evolutions. This paper introduces a numerical variability approach for results stability tests, which determines acceptable variation bounds using random rounding of floating-point calculations.

By applying the resulting stability test to fMRIPrep, a widely-used neuroimaging tool, we show that the test is sensitive enough to detect subtle updates in image processing methods while remaining specific enough to accept numerical variations within a reference version of the application. This result contributes to enhancing the reliability and reproducibility of data analyses by providing a robust and flexible method for stability testing.

Authors

  • Yohan Chatelain
  • Loic Tetrel
  • Christopher J. Markiewicz
  • Mathias Goncalvez
  • Gregory Kiar
  • Oscar Esteban
  • Pierre Bellec
  • Tristan Glatard