mlton VS ante

https://github.com/MLton/mlton/issues/473

Is there sufficient use of MLTon "native" backend out there to consider it mature? or Do people prefer the LLVM or C backend instead in general?

Once I got the parser ready in OCaml, I thought I port it to Standard ML, since it belong to the same ML language family. I was also curious on how well mlton could optimise it. The language lacks custom let bindings, so I resorted to use Result.bind manually. This makes code much less readable and more verbose. The standard library also lacks result type, so I had to come up with my own simple implementation. There's also a lack of any hash map in the standard library, so I just used a list of key-value pairs. This isn't correct, but it's the closest I could get without inventing my own hash map. MLton's compile times are slow. It also lacks interactive REPL. Because of that I used alternative Standard ML implementation for interactive usage: PolyML. Debugging MLton binaries is also pretty hard. gdb doesn't work and there's no bundled debugger. I had to resort to debugging facilities built into PolyML. Valgrind doesn't work with mlton binaries, as it doesn't report any memory allocations. Looks like mlton uses mmap for allocation memory. Surprisingly, performance is not the best. This might be due to heavy usage of my custom Result type and bind calls. Exceptions seem to be a more natural choice for error reporting in Standard ML. I tried to make such a change, but this didn't improve the performance much.

MLton

Something I’d highly recommend you do before concluding that SML’s module system is the best is to go through and read the MLton Basis library. MLton uses the module system extremely heavily in its definition of the standard, and I think it’s extremely important to understand what you may be getting yourself into when you add those features, and what you may lose in return.

If you’re fine with tracing GC (which depends on the situation, of course), Standard ML is a perfectly boring language (that IIUC predated and inspired Caml) and MLton[1] is a very nice optimizing compiler for it. The language is awkward at times (in particular, the separate sublanguage of modules can be downright unwieldy), and the library has some of the usual blind spots such as nonexistent Unicode support (well, not every language WG is allocated a John Cowan).

Speaking of, Scheme can also be a delightful unexciting static language; consider for example the C-producing implementation Chicken[2]. The pattern-matching / algebraic-datatype story was still rather unsatisfying last I checked, but there are other situations where it shines—it’s complementary to SML in a way.

You’re not going to be writing a kernel or a real-time renderer in either (though I’m certain people have taken that as a challenge), they son’t afford the flashy EDSLs of Tcl, Ruby, or Racket, and I can’t say I can prototype in them like I do in Python or sh+tools, but there is a comfortable middle ground where they fit well. (I hear others use Go in what seem like the same places, but to me it feels so thin and devoid of joy that I can’t really compare.)

The FFI tools in both of the mentioned implementations are excellent, though not quite at the “type in C declarations” level of LuaJIT and D.

[1] http://mlton.org/

[2] https://call-cc.org/

Unfortunately, I haven't found a ton of "easily-digestible" and, at the same time, comprehensive guides on compiling functional languages. Generally you'll find a mix of blog posts/class notes/papers covering a single step.

Some resources I like:

- Andrew Kennedy's 2007 paper Compiling with Continuations, Continued [1]. This one is the most clear IMO

- Andrew Appel's Compiling with Continuations book (a bit outdated though... assembly code is for VAX)

- Matt Might's series [2]

- MLton's source and documentation [3]

[1] https://www.microsoft.com/en-us/research/wp-content/uploads/...

[2] https://matt.might.net/articles/closure-conversion/

[3] http://mlton.org/

More broadly, they can be fast even without such extensions if they aggressively pursue optimization opportunities afforded by static typing, like MLton for example, but that also impacts compilation performance negatively.

https://github.com/MLton/mlton/blob/master/lib/mlton/basic/hash-set.sig https://github.com/MLton/mlton/blob/master/lib/mlton/basic/hash-table.sig

Have you had a look at Ante? It looks a lot like a Rust 2.0 with better ergonomics. There are a lot of interesting ideas.

Ante is what you are looking for. It's an ML descendant with no RTS nor AGC.

In my experience, people believe that programming languages are a solved space, and we should stick with what we have.

It's unfortunate; because languages are very polarized today. I think there's a lot of room for languages that are safe, fast, and most importantly, *easy.* Today's languages are generally two out of three.

Luckily, a lot of languages are exploring that space!

* Vale is blending generational references with regions, to have memory-safe single ownership without garbage collection or a borrow checker. [0]

* Cone is adding a borrow checker on top of GC, RC, single ownership, and even custom user allocators. [1]

* Lobster found a way to add borrow-checker-like static analysis to reference counting. [2]

* HVM is using borrowing and cloning under the hood to make pure functional programming ridiculously fast. [3]

* Ante is using lifetime inference and algebraic effects to make programs faster and more flexible. [4]

* D is adding a borrow checker!

[0] https://verdagon.dev/blog/zero-cost-refs-regions

[1] https://cone.jondgoodwin.com/

[2] https://www.strlen.com/lobster/

[3] https://github.com/Kindelia/HVM

[4] https://antelang.org/

[Ante](https://antelang.org/): lifetime inference, refinement types, algebraic effects.