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Thinking about the difference, I wonder if there is a PBT framework that would exploit feedback like fuzzing does, to improve coverage.


The Choice Gradient Sampling algorithm shown in the paper could be used to integrate/exploit feedback (coverage, etc.).

Hypothesis can use a fuzzer as its input source, but it's marked as experimental.

It doesn't seem like "proper" fuzzers are used very often with Haskell (e.g. there's an example at https://www.tweag.io/blog/2023-06-15-ghc-libfuzzer/ ), though many people seem to have hooked up the HPC code coverage tool to property checkers, e.g.

https://www.cse.iitk.ac.in/users/karkare/MTP/2011-12/subhash...

https://www.doc.ic.ac.uk/~tora/irulan/issta.pdf

https://github.com/shapr/kudzu




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