## Promoting functions to type families in Haskell

It’s been very quiet on the blog these past few months not because I’m spending less time on functional programming but precisely for the opposite reason. Since January I’ve been working together with Richard Eisenberg to extend his `singletons`

library. This work was finished in June and last Friday I gave a talk about our research on Haskell Symposium 2014. This was the first time I’ve been to the ICFP and Haskell Symposium. It was pretty cool to finally meet all these people I know only from IRC. I also admit that the atmosphere of the conference quite surprised me as it often felt like some sort of fan convention rather than the biggest event in the field of functional programming.

The paper Richard and I published is titled “Promoting Functions to Type Families in Haskell”. This work is based on Richard’s earlier paper “Dependently typed programming with singletons” presented two years ago on Haskell Symposium. Back then Richard presented the `singletons`

library that uses Template Haskell to generate singleton types and functions that operate on them. Singleton types are types that have only one value (aside from bottom) which allows to reason about runtime values during compilation (some introduction to singletons can be found in this post on Richard’s blog). This smart encoding allows to simulate some of the features of dependent types in Haskell. In our current work we extended promotion capabilities of the library. Promotion is only concerned with generating type-level definitions from term-level ones. Type-level language in GHC has become quite expressive during the last couple of years but it is still missing many features available in the term-level language. Richard and I have found ways to encode almost all of these missing features using the already existing type-level language features. What this means is that you can write normal term-level definition and then our library will automatically generate an equivalent type family. You’re only forbidden from using infinite terms, the `do`

-notation, and decomposing `String`

literals to `Char`

s. Numeric literals are also very problematic and the support is very limited but some of the issues can be worked around. What is really cool is that our library allows you to have partial application at the type level, which GHC normally prohibits.

You can learn more by watching my talk on YouTube, reading the paper or the `singletons`

documentation. Here I’d like to add a few more information that are not present in the paper. So first of all the paper was concerned only with promotion and didn’t say anything about singletonization. But as we enabled more and more language constructs to be promoted we also made them singletonizable. So almost everything that can be promoted can also be singletonized. The most notable exception to this rule are type classes, which are not yet implemented at the moment.

An interesting issue was raised by Adam Gundry in a question after the talk: what about difference between lazy term-level semantics and strict type-level semantics? You can listen to my answer in the video but I’ll elaborate some more on this here. At one point during our work we were wondering about this issue and decided to demonstrate an example of an algorithm that crucially relies on laziness to work, ie. fails to work with strict semantics. I think it’s not straightforward to come up with such an algorithm but luckily I recalled the backwards state monad from Philip Wadler’s paper “The essence of functional programming”^{1}. Bind operator of that monad looks like this (definition copied from the paper):

m `bindS` k = \s2 -> let (a,s0) = m s1 (b,s1) = k a s2 in (b,s0) |

The tricky part here is that the output of call to `m`

becomes input to call to `k`

, while the output of call to `k`

becomes the input of `m`

. Implementing this in a strict language does not at all look straightforward. So I promoted that definition expecting it to fail spectacularly but to my surprised it worked perfectly fine. After some investigation I understood what’s going on. Type-level computations performed by GHC are about constraint solving. It turns out that GHC is able to figure out in which order to solve these constraints and get the result. It’s exactly analogous to what happens with the term-level version at runtime: we have an order of dependencies between the closures and there is a way in which we can run these closures to get the final result.

All of this work is a small part of a larger endeavour to push Haskell’s type system towards dependent types. With singletons you can write type-level functions easily by writing their definitions using the term-level language and then promoting these definitions. And then you can singletonize your functions to work on singleton types. There were two other talks about dependent types during the conference: Stephanie Weirich’s “Depending on Types” keynote lecture during ICPF and Richard’s “Dependent Haskell” talk during Haskell Implementators Workshop. I encourage everyone interested in Haskell’s type system to watch both of these talks.