Within the last couple years, I've become fascinated by the ML family of languages. First I learned OCaml, and recently began SML/NJ, but there's a notable lack of decent tooling for them, mostly the latter. I intend for the culmination of my time exploring ML to be the implementation of a compiler for an ML dialect I will design for writing compilers, probably inspired by Andreas Rossberg's 1ML, but before I reach a point where I feel prepared to start such a project, likely in a couple more years, I'd like to further familiarize myself with these languages and help rectify the tooling problem by writing an LSP implementation for SML. I'm going to be writing this in F#, a very well-tooled language and the only major ML I haven't touched on OCaml, probably.

In light of all this, I have a couple questions for you:

1. I've never actually written a language server before, but I imagine it goes something like this: write a lexer, parser, and semantic-analyzer, then take the output of that last stage as input to a collection of functions exposed to a programmer via the editor interface to the LSP API. I have the LSP spec to reference, so I'm sure I can figure this last part out. Does this all sound reasonable?

2. I think the first two "compiler" stages should be mostly trivial with a lexer/parser generator and the SML '97 spec on hand. That just leaves the semantic-analysis, which is the hardest part anyway. Do you have any tips or resources for someone implementing SML semantic analysis?

3. Finally, any general advice about ML languages, ideas for the SML LS, or something else? I'd love to hear it.

Thanks!

• Release notes: https://smlnj.org/dist/working/2021.1/2021.1-README.html

• Change log: https://www.smlnj.org/dist/working/2021.1/HISTORY.html

This is the first SML/NJ version to use LLVM for code generation. This is a beta release.

I wonder why the release date is "December 32, 2021".

Hey /r/sml! I've been meaning to put in writing some more accessible guides (e.g. not PDFs) on Standard ML, the language, and I finally got around to it. The first three chapters of this "ebook" are available at ponyo.org/guides. I started meaningfully 1-2 weeks ago and I've been writing at least one chapter a week.

There's definitely a lot that could be missing, confusing, or just wrong. But there's now just enough content that it feels worth letting people outside my Twitter followers know. :)

Whether you're interested in learning more about Standard ML or critiquing my writing, I'd love your feedback!

PolyML 5.8.2 Release: FFI is very fast now. Faster 4 - 16 times.