Java can also have 15+ minute cold compiles on large projects if you kill all caches. It's less bad on smaller codebases because you don't have to recompile dependencies if you target a bytecode vm, but if you always gate feedback on a cold compile in a fresh VM you just aren't gonna beat an interpreted language
But I'd look at people a bit oddly if they said: 'We didn't want to set up CI caching and compiled languages took 30 minutes per run so we changed our entire codebase to python'.
Maybe it makes sense for them, and caching across dynamically spawned VM's is admittedly a harder problem which most build systems aren't great at, but still. I can easily believe that getting build caching to be reliable would be a lot of work, but is it more work than a full rewrite of a significant codebase?
Having pair programmed over some truly awful and locked down connections before, dropped frames are infinitely better than blurred frames which make text unreadable whenever the mouse is moved. But 40mbps seems an awful lot for 1080p 60fps.
Temporal SVC (reduce framerate if bandwidth constrained) is pretty widely supported by now, right? Though maybe not for H.264, so it probably would have scaled nicely but only on Webrtc?
I think WasmGC is very hard to make work with laziness.
A lazy value is always a closure on the heap.
If an expression might be unused, throw a closure which computes it on the heap
If the value is actually needed, invoke the closure. Optionally replace the closure with a black hole. A black hole is just a closure which pauses any thread which calls it, to be resumed once the first thread finishes with the expression
Once finished, replace with a closure which immediately returns the computation result. (Or often save the indirection because most concrete values also act as closures which immediately returns themselves using info table pointers trickery)
Anyway, iirc WasmGC wants very rigid types without dynamic type changes. Extra indirections could fix that, Oor maybe defunctionalizing thunks into a tagged union, but both sound expensive. Especially without being able to hook into the tracing step for indirection removal.
Also, Haskell supports finalizers so WasmGC would need that as well.
Sometimes keeping a fixed shape for the variable context across the computation can make it easier to reason about invariants, though.
Like, if you have a constraint is_even(x) that's really easy to check in your head with some informal Floyd-Hoare logic.
And it scales to extracting code into helper functions and multiple variables. If you must track which set of variables form one context x1+y1, x2+y2, etc I find it much harder to check the invariants in my head.
These 'fixed state shape' situations are where I'd grab a state monad in Haskell and start thinking top-down in terms of actions+invariants.
To me the big winning is that you don't have to memoize transitively. Occasionally someone asks me for help to optimize some react code, and then the dependency array contains some object/callback that has a dependency which has a dependency which wasn't memoized.
- you cannot compare objects and functions for semantic equality
If you wrote larger react apps you almost certainly had to useCallback at some point so that memoization worked, the compiler fixes that.
Whenever you construct an object or function the react compiler memoizes on their free variables so pointer equality is sufficient.
Though I do think the compiler caches too aggressively, even if there are no free variables and hoisting is sufficient or escape analysis shows it is unnecessary for semantics.
That is probably good advice but this style of coding
(which comes down to lawless type classes without inherent utility) does make it much more difficult to read unknown code.
Usually documentation isn't fleshed out in internal modules so I end up flipping between various instances and call sides just to figure out what the type class is supposed to do. This doesn't mean that there aren't valid use cases for this but please don't use it as default.
But I'd look at people a bit oddly if they said: 'We didn't want to set up CI caching and compiled languages took 30 minutes per run so we changed our entire codebase to python'.
Maybe it makes sense for them, and caching across dynamically spawned VM's is admittedly a harder problem which most build systems aren't great at, but still. I can easily believe that getting build caching to be reliable would be a lot of work, but is it more work than a full rewrite of a significant codebase?