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Algorithmic chip-design loops

Do input-biased random vectors (extreme, sparse, one-hot) catch RTL bugs that uniform random vectors never did?

research/eda-biasdraw

Four biased generators (20,000 vectors per target) catch none of the 26 eda-deepdraw survivors, so none contradicts a formal equivalence proof, and the del@122 mutant is confirmed as truncated output (90 rows for 100 vectors).

5 tests

What it found

Extreme-value, sparse, one-hot and mixed input generators, 5,000 vectors each, run against the 26 eda-deepdraw targets (16 proved equivalent, 9 formal timeouts, plus del@122). No generator catches any of them, so none of the 16 equivalence proofs is contradicted, and a bug visible to a given generator among the 9 undecided mutants has per-vector detection probability below 6×10−4 (95%). The del@122 mutant prints 90 output rows for 100 vectors with no wrong value, confirming truncation. Stylised and negative: one design, hand-chosen generators.

Paper, code and results

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Produced with AI assistance (Claude). Results are from the code in this repository and are simulated or stylised unless the abstract says otherwise; nothing here implies affiliation with or endorsement by any lab, researcher or company cited. MIT licensed.