I'd argue there is a certain notion of fuzzing with proofs. Say I have a proof claiming that a certain function is monotonic. Fuzzing, in this case, is throwing a bunch of numbers at the function and checking to see if it's actually monotonic with regards to your inputs.
Obviously not all math proofs are regarding functions and definable numbers, but there's a similar concept of fuzzing for each different proof type -- it just might not be easy to automate, or state in a programming language.
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I'd argue there is a certain notion of fuzzing with proofs. Say I have a proof claiming that a certain function is monotonic. Fuzzing, in this case, is throwing a bunch of numbers at the function and checking to see if it's actually monotonic with regards to your inputs.
Obviously not all math proofs are regarding functions and definable numbers, but there's a similar concept of fuzzing for each different proof type -- it just might not be easy to automate, or state in a programming language.
There are some domains, like Geometry, where trying enough random numbers is actually good enough for a certain kind of proof.