proptest VS Clippy

proptest: Property-based testing with random input generation.

Isn't proptest something that could handle this?

https://github.com/proptest-rs/proptest

Proptest is a Rust crate for property-based testing. Recently I wanted/needed to manually implement a proptest strategy for my own type, and I realized that there is not that much material on how to do it. So I wrote a post where I tried to describe what I learned. It's a bit niche, but I hope that someone at some point will find it useful.

Take a look at proptest.

Yes exactly, you can also add to this fuzzing and property based testing.

proptest is great! It generates random input data according to some rules, and if the input fails it saves random seed into a file so that failing inputs are guaranteed to be tested on the subsequent runs (as well as new random inputs). It also doesn't immediately stop on fail but tries to find a minimal failing input first.

The only other crate I could find is proptest, but it looks a lot more complicated, and I don't know if lets you skip the shrinking step as quickcheck does. I've been reading the book and going through the docs, but a quick answer would be appreciated.

We just released proptest 1.1.0, a property-testing framework for Rust. Proptest has recently found new maintainers, and this marks the first new release of proptest in ~2 years.

Hi, I'm working on a fuzzer, that fuzzes APIs based on OpenAPI specification. I'd like to implement shrinking. It means that when an interesting input (for the API) is found, I'd like to create the smallest possible input that still causes the same behaviour of the API. I'd like to implement a payload generation via proptest, because it already has the shrinking ability. I'm having issues implementing the JSON object as a proptest strategy. Here is what I tried so far. I explained it in a detail in stackoverflow question but it did not reach many people. Thanks for your help!

Third, if you're opting out of a compile-time safety guarantee in the name of performance, test heavily (high-coverage unit tests, property testing, fuzzing, differential fuzzing, etc.) and make use of tools like Loom and Miri's runtime data race detector for unsafe code, which can catch stuff that is beyond the scope of the compiler's guarantees.

Firstly, I added a section to run the code formatter rustfmt and the linter clippy:

I couldn't find it in the API guidelines either. From what I understand, the idea is that any trait bounds, which includes generic type parameter bounds and lifetime bound on a type (struct or enum) would be repeated back in the impl block

there is a nice discussion on this issue here: https://github.com/rust-lang/rust-clippy/issues/1689

You should not blindly follow clippy lints. They are sometimes wrong. Another example https://github.com/rust-lang/rust-clippy/issues/9782 .

I often write () = f() to assert that f() is unit. Unfortunately clippy warns on such code ( https://github.com/rust-lang/rust-clippy/issues/9048 ). There are very recent pull requests for this bug, so hopefully this bug will be fixed very soon. But meanwhile I invented this workaround: [()] = [f()] :)

Apart from running clippy on many projects being essential, clippy is also an exceptionally welcoming project, no matter your prior knowledge.

clippy is a great place to get started :) though it isn't exactly new.

clippy is also pretty compiler-adjacent and unlike rust-analyzer uses rustc's internal APIs. Don't let the size of the code base scare you off! It's actually feasible for a newcomer to contribute even such a substantial change as a new lint, and we have issues labeled as "good first issue" that come with mentorship, so you don't need to go it alone.

Yes, you could use it to write a lint. Although you might find it easier to just fork Clippy and add your own lints to their existing framework.

Check out the readme for more information.