> On Jan 4, 2020, at 20:38, Richard Eisenberg <[email protected]> wrote:
>
> I thought that, maybe, we could use partial improvement to give you what you
> want
I think that improvement alone cannot possibly be enough here, as improvement
by its nature does not provide evidence. Improvement allows us to take a set of
constraints like
[G] FD2 a Bool
[W] FD2 a b
and derive [WD] b ~ Bool, but importantly this does not produce a new given!
This only works if b is a metavariable, since we can solve the new wanted by
simply taking b := Bool, but if b is rigid, we are just as stuck as before. In
other words, improvement only helps resolve ambiguities, not derive any new
information.
That’s why I think the “superclass” characterization is more useful. If instead
we express your FD2 class as
class b ~ B a => FD2 a b where
type B a
then if we have [G] FD2 a Bool, we can actually derive [G] B a ~ Bool, which is
much stronger than what we were able to derive using improvement.
I imagine you are aware of all of the above already, but it’s not immediately
clear to me from your description why you need functional dependencies (and
therefore improvement) rather than this kind of approximation using
superclasses and type families. Would modeling things with that approximation
help at all? If not, why not? I think that would help me understand what you’re
saying a little better.
Thanks,
Alexis
_______________________________________________
ghc-devs mailing list
[email protected]
http://mail.haskell.org/cgi-bin/mailman/listinfo/ghc-devs
