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@dwijnand dwijnand linked an issue Jan 29, 2023 that may be closed by this pull request
// Skip = minimisedSelected "hold off instantiating"
// False = return false

// there are 9 combinations:
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I love this documentation!

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@odersky odersky left a comment

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Very nice tests and docs! And the actual change is correct, of course.

EDIT: I think I commented too fast, and now see problems with the second change.

// else hold off instantiating unbounded unconstrained variable
else if direction != 0 then
instantiate(tvar, fromBelow = direction < 0)
else if variance >= 0 && (force.ifBottom == IfBottom.ok || tvar.hasLowerBound) then
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@odersky odersky Aug 7, 2023

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There's no motivation why the !tvar.hasUpperBound is added. It does not make sense to me. IfBottom being ok means we are allowed to minimize to Nothing. Why stop doing this if there is an upper bound?

I agree that the issue this fixes is a real one. But I am missing the reasoning why this PR is the correct fix, in particular since the PR caused regressions elsewhere.

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From the logic it seems we're happy to minimise if there's a lower bound and maximise if there's a lower bound. IfBottom, to me, looks like it's mostly for it's IfBottom.fail and IfBottom.flip alternatives - as in, IfBottom.ok is the "default"/"standard" behaviour. So under that condition, we don't want to minimise when we have an upper bound. Doing so causes the issue we're trying to fix: we have a S1 <: Pet parameter, and there are no further constraints. Consistently with everything else, it should maximise to Pet, not minimise to Nothing.

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The way I read it is: If the lower bound is (missing or) Nothing then we are allowed to instantiate to the lower bound only if isBottom is OK. The upper bound has nothing to do with it.

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I don't understand what justifies ignoring an existing upper bound, which is exactly the i14218 case.

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@odersky odersky Aug 7, 2023

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I had a closer look at it now. Here's a slight adaptation of the original issue:

class A
class B extends A

class Z[S](v: S => Unit)
val x = new Z((s: B) => ())

x has type Z[B], as expected.

Now add a bound to S:

class Z[S <: A](v: S => Unit)

x still has type Z[B]!

But if we sharpen the bound to B:

class Z[S <: B](v: S => Unit)

then x has type Z[Nothing].

The reason this happens is because of code in Inferencing before the line in question:

            val direction = instDirection(tvar.origin)
            ...
            else if direction != 0 then
              instantiate(tvar, fromBelow = direction < 0)

The direction is set to -1 if the variable is constrained only from below and to 1 if the variable is constrained only from above. "Is constrained" means: There is a constraint stronger than the variable's bound. That's what goes wrong here: The added constrant is exactly the variable's bound, so it does not count. It's hard to change this, since the information that we also added a constraint (not just recorded the bound) is lost if the constraint is not stronger than the bound.

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Upper bound makes compiler infer Nothing

4 participants