Proving Commutativity of Polysemy Interpreters

To conclude this series of posts on polysemy-check, today we’re going to talk about how to ensure your effects are sane. That is, we want to prove that correct interpreters compose into correct programs. If you’ve followed along with the series, you won’t be surprised to note that polysemy-check can test this right out of the box.

But first, what does it mean to talk about the correctness of composed interpreters? This idea comes from Yang and Wu’s Reasoning about effect interaction by fusion. The idea is that for a given program, changing the order of two subsequent actions from different effects should not change the program. Too abstract? Well, suppose I have two effects:

foo :: Member Foo r => Sem r ()
bar :: Member Bar r => Sem r ()

Then, the composition of interpreters for Foo and Bar is correct if and only if1 the following two programs are equivalent:

forall m1 m2.
  m1 >> foo >> bar >> m2
  m1 >> bar >> foo >> m2

That is, since foo and bar are actions from different effects, they should have no influence on one another. This sounds like an obvious property; effects correspond to individual units of functionality, and so they should be completely independent of one another. At least — that’s how we humans think about things. Nothing actually forces this to be the case, and extremely hard-to-find bugs will occur if this property doesn’t hold, because it breaks a mental abstraction barrier.

It’s hard to come up with good examples of this property being broken in the wild, so instead we can simulate it with a different broken abstraction. Let’s imagine we’re porting a legacy codebase to polysemy, and the old code hauled around a giant stateful god object:

data TheWorld = TheWorld
  { counter :: Int
  , lots    :: Int
  , more'   :: Bool
  , stuff   :: [String]

To quickly get everything ported, we replaced the original StateT TheWorld IO application monad with a Member (State TheWorld) r constraint. But we know better than to do that for the long haul, and instead are starting to carve out effects. We introduce Counter:

data Counter m a where
  Increment :: Counter m ()
  GetCount :: Counter m Int

makeSem ''Counter

with an interpretation into our god object:

    :: Member (State TheWorld) r
    => Sem (Counter ': r) a
    -> Sem r a
runCounterBuggy = interpret $ \case
  Increment ->
    modify $ \world -> world
                         { counter = counter world + 1
  GetCount ->
    gets counter

On its own, this interpretation is fine. The problem occurs when we use runCounterBuggy to handle Counter effects that coexist in application code that uses the State TheWorld effect. Indeed, polysemy-check tells us what goes wrong:

quickCheck $
  prepropCommutative @'[State TheWorld] @'[Counter] $
    pure . runState defaultTheWorld . runCounterBuggy

we see:


Effects are not commutative!

k1  = Get
e1 = Put (TheWorld 0 0 False [])
e2 = Increment
k2  = Pure ()

(k1 >> e1 >> e2 >> k2) /= (k1 >> e2 >> e1 >> k2)
(TheWorld 1 0 False [],()) /= (TheWorld 0 0 False [],())

Of course, these effects are not commutative under the given interpreter, because changing State TheWorld will overwrite the Counter state! That’s not to say that this sequence of actions actually exists anywhere in your codebase, but it’s a trap waiting to happen. Better to take defensive action and make sure nobody can ever even accidentally trip this bug!

The bug is fixed by using a different data store for Counter than TheWorld. Maybe like this:

    :: Sem (Counter ': r) a
    -> Sem r a
runCounter = (evalState 0) . reinterpret @_ @(State Int) $ \case
  Increment -> modify (+ 1)
  GetCount -> get

Contrary to the old handler, runCounter now introduces its own anonymous State Int effect (via reinterpret), and then immediately eliminates it. This ensures the state is invisible to all other effects, with absolutely no opportunity to modify it. In general, this evalState . reintrpret pattern is a very good one for implementing pure effects.

Of course, a really complete solution here would also remove the counter field from TheWorld.

Behind the scenes, prepropCommutative is doing exactly what you’d expect — synthesizing monadic preludes and postludes, and then randomly pulling effects from each set of rows and ensuring everything commutes.

At first blush, using prepropCommutative to test all of your effects feels like an O(n2)O(n^2) sort of deal. But take heart, it really isn’t! Let’s say our application code requires Members (e1 : e2 : e3 : es) r, and our eventual composed interpreter is runEverything :: Sem ([e] ++ es ++ [e3, e2, e1] ++ impl) a -> IO (f a). Here, we only need O(es)O(es) calls to prepropCommutative:

  • prepropCommutative @'[e2] @'[e1] runEverything
  • prepropCommutative @'[e3] @'[e2, e1] runEverything
  • prepropCommutative @'[e] @'(es ++ [e2, e1]) runEverything

The trick here is that we can think of the composition of interpreters as an interpreter of composed effects. Once you’ve proven an effect commutes with a particular row, you can then add that effect into the row and prove a different effect commutes with the whole thing. Induction is pretty cool!

As of today there is no machinery in polysemy-check to automatically generate this linear number of checks, but it seems like a good thing to include in the library, and you can expect it in the next release.

To sum up these last few posts, polysemy-check is an extremely useful and versatile tool for proving correctness about your polysemy programs. It can be used to show the semantics of your effects (and adherence of such for their interpreters.) It can show the equivalence of interpreters — such as the ones you use for testing, and those you use in production. And now we’ve seen how to use it to ensure that the composition of our interpreters maintains its correctness.

Happy testing!

  1. Well, there is a second condition regarding distributivity that is required for correctness. The paper goes into it, but polysemy-check doesn’t yet implement it.↩︎