Similarly, the ‘indirect’ keyword can be omitted from Swift example in the blog post, for the same reason. A Swift Array stores its elements out of line, so an enum case payload can be an array type whose element contains the same enum, without any additional indirection.
I wasn’t trying to start a fight over languages, that would be silly. I also wrote a language once and then moved on from it (to your former language ;-)), so I know the feeling! I wish you luck with your new language, and I wish for many more languages in the future to try different approaches and learn from each other.
My original reply was just to point out that constraint solving, in the abstract, can be a very effective and elegant approach to these problems. There’s always a tradeoff, and it all depends on the combination of other features that go along with it. For example, without bidirectional inference, certain patterns involving closures become more awkward to express. You can have that, without overloading, and it doesn’t lead to intractability.
> Bidirectional constraint solving. It's bad for compile time but even worse for predictable diagnostics.
That’s really only true if you have overloading though! Without overloading there are no disjunction choices to attempt, and if you also have principal typing it makes the problem of figuring out diagnostics easier, because each expression has a unique most general type in isolation (so your old CSDiag design would actually work in such a language ;-) )
But perhaps a language where you have to rely on generics for everything instead of just overloading a function to take either an Int or a String is a bridge too far for mainstream programmers.
So what did you decide to give up on? Overloading functions with the same name, or bidirectional constraint solving? :)
These days though the type checker is not where compile time is mostly spent in Swift; usually it’s the various SIL and LLVM optimization passes. While the front end could take care to generate less redundant IR upfront, this seems like a generally unavoidable issue with “zero cost abstraction” languages, where the obvious implementation strategy is to spit out a ton of IR, inline everything, and then reduce it to nothing by transforming the IR.
> Still fails on a very recent version of Swift, Swift 6.1.2, if my test works.
FWIW, the situation with this expression (and others like it) has improved recently:
- 6.1 fails to type check in ~4 seconds
- 6.2 fails to type check in ~2 seconds (still bad obviously, but it's doing the same amount of work in less time)
- latest main successfully type checks in 7ms. That's still a bit too slow though, IMO. (edit: it's just first-time deserialization overhead; if you duplicate the expression multiple times, subsequent instances type check in <1ms).
> This has tradeoffs: increased ABI stability at the cost of longer compile times.
Nah. Slow type checking in Swift is primarily caused by the fact that functions and operators can be overloaded on type.
Separately-compiled generics don't introduce any algorithmic complexity and are actually good for compile time, because you don't have to re-type check every template expansion more than once.