quickcheck VS Random

Maybe https://github.com/BurntSushi/quickcheck too?

Yeah as other have mentioned, I was using Rust before 1.0.

This is my first public commit: https://github.com/BurntSushi/quickcheck/commit/c9eb2884d6a6...

I didn't write any substantive Rust before that point. So I'm at over 9 years.

The book, Zero To Production In Rust, uses quickcheck:

Hi all! I'm looking for some feedback on my latest crate, reltester. It's a small utility crate that, when paired with property-based testing with e.g. quickcheck makes it very easy to check that your handwritten comparison trait implementations satisfy the necessary constraints (transitivity, reflexivity, and all that stuff). I wrote it our of frustration after finding many subtle bugs in our PartialEq and PartialOrd implementations at $JOB, and hopefully someone else will find it useful.

For what it's worth this would also be a good candidate for property based testing, like with: https://github.com/BurntSushi/quickcheck

I'm aware of Hypothesis and its approach, but the connection between Hypothesis and arbitrary is indeed non-obvious. Even looking over the API docs again, the most I could pick up was this on the docs of Unstructured:

Quickcheck https://github.com/BurntSushi/quickcheck

I'm running into a strange issue while using [quickcheck](https://github.com/BurntSushi/quickcheck) to implement tests and I'm hoping someone here might have an idea. Long story short, I have tests which fail in weird ways when using quickcheck that I can't reproduce otherwise, so I'm not even sure if it's a legitimate issue or not.

Sure here is a an example (repository) (click "run" to see it work) contrasting the two in Rust, note that it is not fully symbolic, just the imaginary component. But the immediate advantage one can see is allowing direct computation without needing to modify the polynomial multiplication algorithm. (As noted in the source code, this is a purely theoretical advantage).

I can't help you with the specific website, but here's a trivial cli implementation of Game of Life.

I've been sitting on my hands when it comes to updating my library, but if you really want a fast test, you can use some of my research/implementation for RCPrime, with creditation of course. I'm not sure what algorithms FLINT uses, but I'm fairly certain that the RCPrime implementation is the most efficient for integers less than 2^35 (requiring 64 multiplications and only one strong fermat test) even if you implement with Montgomery exponentiation.

Here is a sample implementation along with the inverses of the first 128 primes (in hex). (Except 2, which can be easily checked by the &1 trick)

Not what one normally considers in CS, but producing a fast deterministic test for checking primality in the interval 0;2^64 with some extensions beyond. Fully constructing one to 2^128 is well beyond what is currently computable, however some progress has been made that surpasses published bounds.

Working on developing a faster and smaller primality check in the interval 0;2^64 with tentative extensions towards 2^65. While it performs satisfactorily for the intervals currently available, reducing the memory to less than other implementations is a major challenge.

See this other approach for a similar engine, that utilizes a linear bitvector to model cellular automata.

You are way overthinking it. For something like minesweeper you can just model an integer lattice, and use either a 1d vector of integers to represent the positions of the mines or a 1d bitvector and check the values in the chebyshev distance of 1 from the point. (If you use integers like in the first example, your system becomes a plane of 2^32, 2^32 dimensions and is bounded by the number of mines (64-bit integers) that can fit in your RAM)

You can look here for some slightly better ways to test for primality (ignore the different language).

RAND calls a hardware source of Johnson-Nyquist noise (basically electric static), and then performs some filtering on it to make sure that it's evenly distributed. There are faster methods, like a simple "linear" rng, but they frequently don't give as good results.