dafny VS rust

Code correctness is a lost art. I requirement to think in abstractions is what scares a lot of devs to avoid it. The higher abstraction language (formal specs) focus on a dedicated language to describe code, whereas lower abstractions (code contracts) basically replace validation logic with a better model.

C# once had Code Contracts[1]; a simple yet powerful way to make formal specifications. The contracts was checked at compile time using the Z3 SMT solver[2]. It was unfortunately deprecated after a few years[3] and once removed from the .NET Runtime it was declared dead.

The closest thing C# now have is probably Dafny[4] while the C# dev guys still try to figure out how to implement it directly in the language[5].

[1] https://www.microsoft.com/en-us/research/project/code-contra...

[2] https://github.com/Z3Prover/z3

[3] https://github.com/microsoft/CodeContracts

[4] https://github.com/dafny-lang/dafny

[5] https://github.com/dotnet/csharplang/issues/105

I don't think something that specific exists. There are a very large number of formal methods tools, each with different specialties / domains.

For verification with proof assistants, [Software Foundations](https://softwarefoundations.cis.upenn.edu/) and [Concrete Semantics](http://concrete-semantics.org/) are both solid.

For verification via model checking, you can check out [Learn TLA+](https://learntla.com/), and the more theoretical [Specifying Systems](https://lamport.azurewebsites.net/tla/book-02-08-08.pdf).

For more theory, check out [Formal Reasoning About Programs](http://adam.chlipala.net/frap/).

And for general projects look at [F*](https://www.fstar-lang.org/) and [Dafny](https://dafny.org/).

Dafny and Whiley are two examples with explicit verification support. Idris and other dependently typed languages should all be rich enough to express the required predicate but might not necessarily be able to accept a reasonable implementation as proof. Isabelle, Lean, Coq, and other theorem provers definitely can express the capability but aren't going to churn out much in the way of executable programs; they're more useful to guide an implementation in a more practical functional language but then the proof is separated from the implementation, and you could also use tools like TLA+.

https://dafny.org/

https://whiley.org/

https://www.idris-lang.org/

https://isabelle.in.tum.de/

https://leanprover.github.io/

https://coq.inria.fr/

http://lamport.azurewebsites.net/tla/tla.html

> I think we can assume it won't be as efficient has hand written code

Actually, surprisingly, not necessarily the case!

If you'll refer to the discussion in https://github.com/dafny-lang/dafny/issues/601 and in https://github.com/dafny-lang/dafny/issues/547, Dafny can statically prove that certain compiler branches are not possible and will never be taken (such as out-of-bounds on index access, logical assumptions about whether a value is greater than or less than some other value, etc). This lets you code in the assumptions (__assume in C++ or unreachable_unchecked() under rust) that will allow the compiler to optimize the codegen using this information.

The language (Dafny): https://github.com/dafny-lang/dafny

Dafny is a verification-ready programming language. As you type in your program, Dafny's verifier constantly looks over your shoulder, flags any errors, shows you counterexamples, and congratulates you when your code matches your specifications. When you're done, Dafny can compile your code to C#, Go, Python, Java, or JavaScript (more to come!), so it can integrate with your existing workflow.

Most of the proof assistants out there: Lean, Coq, Dafny, Isabelle, F*, Idris 2, and Agda. And the main concepts are dependent types, Homotopy Type Theory AKA HoTT, and Category Theory. Warning: HoTT and Category Theory are really dense, you're going to really need to research them.

I'm not sure if the author is here, or if my comment attempt was successful. So, can I suggest you take a look at a third leg of the formal methods stool?

If you are familiar with C, check out Frama-C (https://frama-c.com/) and the WP and RTE plugins. The approach is based on Tony Hoare and EWD's axiomatic semantics (https://en.wikipedia.org/wiki/Hoare_logic). It does not have a good memory management story, as far as I know, but is very good for demonstrating value correctness (RTE automatically generates assertions for numeric runtime errors, for example) and many memory errors.

If you are familiar with Ada, check out SPARK (https://www.adacore.com/about-spark), which is similar to Frama-C but has a much better interface in the AdaCore GNAT toolkit and IDE.

Both work similarly: Assertions in normal Ada or C code as well as the code itself are translated into SMT statements and fed to a SMT solver to find counterexamples---errors.

I have some blog posts from several years ago about Frama-C:https://maniagnosis.crsr.net/tags/applied%20formal%20logic.h... (And I really should get back into it; it's a lot of fun.)

If you are not familiar with Ada or C, Dafny (https://dafny.org/) is another option based on .NET and devoleped at Microsoft. It seems nigh-on perfect for this approach. (The language uses a garbage collector.) At the time I was looking, there was little documentation on Dafny, but that seems to have improved.

But I suspect that will improve (they're all very new projects). I'm also keeping an eye on Dafny which looks pretty neat and avoids the "oh sorry we don't support traits" issue.

However, if you want the full-fledged powerful code contacts back, you have to go outside C#. The closest you'll get is Dafny. It is a spec language that compiles to C#.

Almost fixed the compiler: https://github.com/rust-lang/rust/pull/123325

Rust: A secure, efficient, and modern programming language (omitting ten thousand words). You can simply follow the installation instructions provided on the official website.

Recently did something similar in Rust but for generating SVGs. We've adopted it for snapshot testing of cargo and rustc's output. Don't have a good PR handy for showing Github's rendering of changes in the SVG (text, side-by-side, swiping) but https://github.com/rust-lang/rust/pull/121877/files has newly added SVGs.

To see what is supported, see the screenshot in the docs: https://docs.rs/anstyle-svg/latest/anstyle_svg/

We strongly believe in Rust as a powerful language for building production-grade software, especially for systems like ours that run alongside Kubernetes.

The above Assert<{N % 2 == 1}> requires #![feature(generic_const_exprs)] and the nightly toolchain. See https://github.com/rust-lang/rust/issues/76560 for more info.

There’s also other reasons. For example, take binary search:

* prefetch + cmov. These should be part of the STL but languages and compilers struggle to emit the cmov properly (Rust’s been broken for 6 years: https://github.com/rust-lang/rust/issues/53823). Prefetch is an interesting one because while you do optimize the binary search in a micro benchmark, you’re potentially putting extra pressure on the cache with “garbage” data which means it’s a greedy optimization that might hurt surrounding code. Probably should have separate implementations as binary search isn’t necessarily always in the hot path.

* Eytzinger layout has additional limitations that are often not discussed when pointing out “hey this is faster”. Adding elements is non-trivial since you first have to add + sort (as you would for binary search) and then rebuild a new parallel eytzinger layout from scratch (i.e. you’d have it be an index of pointers rather than the values themselves which adds memory overhead + indirection for the comparisons). You can’t find the “insertion” position for non-existent elements which means it can’t be used for std::lower_bound (i.e. if the element doesn’t exist, you just get None back instead of Err(position where it can be slotted in to maintain order).

Basically, optimizations can sometimes rely on changing the problem domain so that you can trade off features of the algorithm against the runtime. These kinds of algorithms can be a bad fit for a standard library which aims to be a toolbox of “good enough” algorithms and data structures for problems that appear very very frequently. Or they could be part of the standard library toolkit just under a different name but you also have to balance that against maintenance concerns.

But that said, - and again I might be a bit biased - Groovy is too slow for me! I compared it to Rust in this LinkedIn post and it was waaaaay slow. Keep in mind that subjectively comparing programming languages might be a tricky business. But at the end, it will be up to your use case/project to prefer a language over the other.

13. Rust - $87,012

Yes, actually.

https://github.com/rust-lang/rust/blob/d0ea1d767925d53b2230e...

Limited to the rust codebase itself, but I'm sure the developers would force it on everyone else if they thought they could get away with it.