crubit VS language

See also:

Thomas Neumann's current proposal for memory safe C++ using dependency tracking:

- https://www.open-std.org/jtc1/sc22/wg21/docs/papers/2023/p27...

Google's proposal for memory safety using Rust-like lifetime analysis:

- https://discourse.llvm.org/t/rfc-lifetime-annotations-for-c/...

- https://github.com/google/crubit/tree/main/lifetime_analysis

For the people who are curious: crubit is an attempt to develop the way to seamlessly integrate C++ and Rust.

Please see the experimentation and proposals at https://github.com/google/crubit/blob/main/docs/lifetime_annotations_cpp.md and https://github.com/google/crubit/blob/main/docs/lifetimes_static_analysis.md

autocxx is good, though crubit is aiming for direct bidirectional interop

The areas you mentioned (CLI, web services, low level systems programming) are not mutually exclusive. Doing a good job on one doesn't mean something else is affected.

The folks who worked on the most popular command line argument parser (https://docs.rs/clap/latest/clap/#example) made a positive contribution that didn't detract from any other use case.

Similarly, the folks working on improving Rust for web services will also make it better for systems programming. In a blog post published today (https://blog.rust-lang.org/inside-rust/2022/07/27/keyword-ge...), they discuss keyword generics, a feature that will be equally helpful for `async` code and `const` functions evaluated at compile time.

There is already some interoperability with C++ (http://cxx.rs) and ongoing research into automating this interoperability (https://github.com/google/autocxx, https://github.com/google/crubit). Feels like there's enough effort

This language was started by folks at Google. (Although it's interesting that they're publishing it under a separate github org, which suggests ambitions beyond Google's needs.) Google has a huge, performance-sensitive C++ codebase. At Google, major product teams' backends are typically written in C++, as well as common infrastructure like D (disk server), Colossus (distributed filesystem), Spanner (distributed SQL database), and Borg (cluster management). More than a few people would love for it all to be be written in Rust instead, but migration would be challenging, to say the least. I'm told people are looking into it—see Crubit for example. But AFAIK, no one's decided yet whether Google will stay with C++ for all these things, migrate some to Rust, migrate some to Carbon, and/or do something else entirely.

It's currently unclear if Rust can interop with C++ with high fidelity. For example https://docs.rs/moveit/latest/moveit/ and https://github.com/google/crubit/blob/main/rs_bindings_from_... provide functionality to use non-trivially relocatable C++ types from Rust.

I noticed that I can enable inline-class as an experiment to play with Extension Types. You need to also add sdk: ^3.3.0-0 to your pubspec.yaml.

Current syntax is not all that bad if you are going to do OO and add various helper methods on `Message` and its subclasses, but if you just want to define your data and no behavior / helpers - then it is exceedingly verbose.

[1]: https://github.com/dart-lang/language/issues/3021

Reference

A future version of Dart will probably support macros which should make this all a bit easier to use, similar to how Swift 5.9 works which makes already fantastic use of its new macro capabilities by integrating mobx (or solidjs) like reactivity into SwiftUI by a harmlessly looking @Obervable annotation.

Coming from a Dart context here where that team is also looking at adding Macros to the language. It was really interesting to compare and contrast some of the approaches https://github.com/dart-lang/language/blob/main/working/macr...

Yes, that needs a bit of boilerplate for the constructor declaration and the extra build method, but I personally don't mind and with implicit constructors this will become much easier. Also, you get a performant UI as Flutter knows to not redraw widgets that didn't change.

I know that it would be nice not to use the generator at all, but we have to wait until static metaprogramming is implemented in dart. https://github.com/dart-lang/language/issues/1482

I implemented a prototype version of the algorithm in that paper when exploring exhaustiveness checking for pattern matching in Dart.

I found it pretty easy to understand, but also really easy to get it to generate huge combinatorially large spaces. Some careful memoization and deduplication helped, but even so I never got the performance to a state I considered acceptable.

Instead, I went with Luc Maranget's classic approach and figured out a way to adapt it to a language with subtyping (with a ton of work from Johnni Winther to figure out all of the hard complex cases around generics):

https://github.com/dart-lang/language/blob/main/accepted/fut...

The performance (in the prototype!) was dramatically better. You can always make pattern matching go combinatorial, but I haven't seen any real-world switches get particularly slow with our approach yet, and we have some fairly large tests of matching on tuples of enums.