egg VS JET.jl

Maybe program optimization?

https://egraphs-good.github.io/

For semantic analyzers, check out egg and egglog. They're custom data structures for representing compiler rewrite rules in a non-destructive way.

E-graphs are pretty awesome, and worth keeping in your back pocket. They're like union-find structures, except they also maintain congruence relations (i.e. if `x` and `y` are in the same set, then `f(x)` and `f(y)` must likewise be in the same set).

https://egraphs-good.github.io/

(Incidentally, union-find structures are also great to know about. But they're not exactly "new".)

I would add that Equality saturation/E-graphs has become quite a hot topic recently, since their POPL21 paper, with workshops dedicated to applications of e-graphs. They have even recently been added to Cranelift as an IR for optimizations.

Egraphs solve the rewrite ordering problem quite nicely. https://egraphs-good.github.io/

Note that one solution to this problem is to use equality saturation (which, coincidentally, has a great implementation in rust!).

Have you thought about trying to parallelize e-graphs? This way you can do a bunch of rewrite rules in parallel and then extract your desired graph at the end instead of having conflicts.

I think the equality saturation papers are a good start. A good start is egg. They have a presentation, a research paper and code you can play with. I think ultimately you want to translate arithmetic operations into logical operation that can be understood by the fpga. So I think it would be good to research how adders and multipliers are implemented in logic and ultimately include equalities between adders/multipliers with their logical counterpart. Note the this translation also depends on the representations of your numbers and their bit width.

For rewriting, you may also find interesing equality saturation: https://egraphs-good.github.io/

An informative discussion on julia forum. Have you tried using https://github.com/aviatesk/JET.jl to minimize type instabilities?

For instance, https://github.com/aviatesk/JET.jl is still in its relative infancy, but it's played a big role in detecting quite a few potential bugs that had never been reported to use by users or caught in our testing infrastructure. There's also been a lot developments like interfaces to RR the time travelling debugger https://rr-project.org/ which helps us better understand and catch some very hard to debug non-deterministic bugs.

Have you seen Shuhei Tadowaki's work on JET.jl (?)

If you're curious: https://github.com/aviatesk/JET.jl

This may seem more about performance (than IDE development) but Shuhei is one of the driving contributors behind developing the capabilities to use compiler capabilities for IDE integration -- and indeed JET.jl contains the kernel of a number of these capabilities.

This is sort of being done right now, as dynamic languages have begun to adopt gradual typing... at least Python and Julia, that I know of.

If something like [JET.jl](https://github.com/aviatesk/JET.jl) become ubiquitous in Julia, one could add a function that pointed out all the places in the code where types are not fully inferred by the compiler.

It'll never be quite the same level of safety as a static language, however.

- Pattern matching (sometimes you don't want the overhead of a method lookup)

[1]: https://github.com/aviatesk/JET.jl

You can use the `@code_warntype` macro to check for type stability, which is very helpful for detecting such performance pitfalls on single function level. In the future, https://github.com/aviatesk/JET.jl may give a more powerful way to do it.