inko VS HVM

I have mixed feelings on Rust's syntax, especially around generics, lifetimes, and the `modifier -> keyword` syntax (i.e. `async fn` or `pub fn`). For Inko, I wanted something that's easy to parse by hand, and no context specific parsing (e.g. `QUOTE -> something` being the start of a lifetime in one place, but a char literal in another place).

Another motivator for that is that years ago I worked on Rubinius for a while (an implementation of Ruby), and helped out with a parser for Ruby (https://github.com/whitequark/parser). The Ruby developers really liked changing their already impossible syntax in even more impossible ways on a regular basis, making it a real challenge to provide syntax related tools that support multiple Ruby versions. I wanted to avoid making the same mistake with Inko, hence I'm actively trying to keep the syntax as simple as is reasonable.

As for the specific examples:

- `fn async` means your parser only needs to look for `A | B | fn` in a certain scope, instead of `A | B | fn | async fn`. This cuts down the amount of repetition in the parser. An example is found at https://github.com/inko-lang/inko/blob/8f5ad1e56756fe00325a3..., which parses the body of a class definition.

- Skipping parentheses is directly lifted from Ruby, because I really like it. Older versions took this further by also letting you write `function arg1 arg2`, but I got rid of that to make parsing easier. It's especially nice so you can do things like `if foo.bar.baz? { ... }` instead of `if foo().bar().baz?()`, though I suspect opinions will differ on this :)

- Until recently we did in fact use `::` as a namespace separator, but I changed that to `.` to keep things consistent with the call syntax, and because it removes the need for remembering "Oh for namespaces I need to use ::, but for calls .".

- `[T]` for generics is because most editors automatically insert a closing `]` if you type `[`, but not when you type `<`. If they do, then trying to write `10<20` is annoying because you'd end up with `10<>20`. I also just like the way it looks more. The usual ambiguity issues surrounding `<>` (e.g. what leads to `foo::()` in Rust) doesn't apply to Inko, because we don't allow generics in expressions (i.e. `Array[Int].with_capacity(42)` isn't valid syntax) in the first place.

Inko supports this in its type checker. The implementation is both surprisingly simple and tricky, and works roughly as follows:

Perhaps it's worth looking into Inko? I apologise if I'm shilling my own project a bit too hard here, but reading through the comments it does seem people would be interested in what it's trying to do :)

Perhaps you'd be interested in Inko (https://inko-lang.org/). It's obviously not there yet in terms of tooling and what not, but it might scratch an itch for those looking for something a bit like Rust, but easier to use.

Disclaimer: I'm the author of said language :)

Inko currently uses tagged pointers, though this is a remnant from when it was still using a VM. I'm working on replacing this with a better solution. In short: for a compiled language I don't think there's really a benefit to using pointer tagging.

I think Inko shows this behavior too, where a linear-style program suddenly has zero cost. (Yorick, sanity check me on this?)

For opcodes you can also use a third option: you use a single struct for all opcodes, and size it to support a fixed number of arguments. Most opcodes probably won't need more than 4-5 arguments. If those argument values are small enough (e.g. u16), you don't need that much space. You can find an example of this here, with the Instruction type only taking up 12 bytes.

Reminds me of HVM[0]

[0]https://github.com/HigherOrderCO/HVM

Really interesting to see how new lang concepts and refinements keep popping up this last decade, between Vale, Gleam, Hylo, Austral...

Linear types really opened up lots of ways to improve memory management and compilation improvements.

I have a tangential question that is related to this cool new feature.

Warning: the question I ask comes from a part of my brain that is currently melted due to heavy thinking.

Context: I write a fair amount of Clojure, and in Lisps the code itself is a tree. Just like this F# parallel graph type-checker. In Lisps, one would use Macros to perform compile-time computation to accomplish something like this, I think.

More context: Idris2 allows for first class type-driven development, where the types are passed around and used to formally specify program behavior, even down to the value of a particular definition.

Given that this F# feature enables parallel analysis, wouldn't it make sense to do all of our development in a Lisp-like Trie structure where the types are simply part of the program itself, like in Idris2?

Also related, is this similar to how HVM works with their "Interaction nets"?

https://github.com/HigherOrderCO/HVM

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

https://clojure.org/

I'm afraid I don't even understand what the difference between code, data, and types are anymore... it used to make sense, but these new languages have dissolved those boundaries in my mind, and I am not sure how to build it back up again.

Impressive presentation but I find two things missing in particular:

* GRIN [1] - arguably a breakthrough in FP compilation; there are several implementation based on this

* HVM [2] - parallel optimal reduction. The results are very impressive.

[1] https://link.springer.com/chapter/10.1007/3-540-63237-9_19

[2] https://github.com/HigherOrderCO/HVM

Purity has nothing to do with memoization. Haskell's semantics never "rewrite under a lambda" (unlike, e.g. HVM). Calling (\_ -> e) () twice will (modulo optimizations) always perform the computation in e twice.

The most recent exploration of this, that I'm aware of is HVM (another intermediate language / runtime), although this one is not actually based on the lambda calculus, but on the interaction calculus.

Then, actually unrelated but worth mentioning: HVM. Finally, something new on the functional front that isn't dependent types!

If you are into functional PL, how about https://github.com/HigherOrderCO/HVM? You could experiment if you could schedule that on a GPU?

In the interest of seeking ways of optimizing my code, I stumbled upon http://www.rntz.net/datafun/ as a means to do incremental computations of fixpoints while avoiding redundant work. And also the idea of automatic parallelism achieved by using Interaction Nets as a model of computation https://github.com/HigherOrderCO/HVM.