Perturbation testing
Apply small, meaning-preserving changes to an input — typos, spacing, paraphrase, reordering — and check that the output stays stable. When it doesn't, you've measured brittleness.
Published June 26, 2026
How it works
A robust system should be indifferent to changes that don't change meaning: a stray typo, extra whitespace, a synonym, a reordered clause. Perturbation testing applies these small transformations at scale and flags every case where the answer moves. It is a focused, robustness-oriented cousin of metamorphic testing — the relation is simply 'meaning-preserving in, same answer out' — and it exposes the prompt-sensitivity that quietly undermines reproducibility.
When to use it
Robustness hardening; quantifying prompt-sensitivity; regression-guarding inputs that users will phrase many different ways.
Limitations
You must ensure the perturbation truly preserves meaning — an over-aggressive change creates false positives — and it detects instability, not which of the diverging answers is correct.
Cite this
Qlarify Labs. (2026). Perturbation testing. Retrieved from https://labs.qlarify.fi/catalog/perturbation-testing


