I think if you evolve your testing system to feed random numbers into your program and ensure that various correctness properties hold for all these random inpu

I think if you evolve your testing system to feed random numbers into your program and ensure that various correctness properties hold for all these random inputs you are likely to get a pretty robust program. You can make this slightly efficient by using a fuzzer (essentially uses feedback from running previous inputs to see how running new inputs works). See for example https://propertesting.com/ https://propertesting.com/ or https://en.wikipedia.org/wiki/American_Fuzzy_Lop_(software) https://en.wikipedia.org/wiki/American_Fuzzy_Lop_(software) Of course if you need a higher standard of guarantee you can try model checking or other formal verification techniques.