1. Supercompilation and Normalisation by Evaluation Gavin Mendel-Gleason & Geoff Hamilton Lero@DCU Dublin City University

2. Why Bother? Wanted to figure out when one thing was like another. Thought that Supercompilation's intuitive process trees might have a deeper meaning. Normalisation is a well used framework for finding canonical terms Normalisation is stuck in a terminating world

3. Normalisation In the Curry Howard setting, normalisation is cut elimation and proof simplification. We can tell if two proofs are the same if they are synatically identical after normalisation. Normalisation just requires the application of appropriate reduction rules.

4. Curry-Howard Correspondance We try to draw a correspondance between the world of proofs and the world of programs Proofs Programs Propositions Types

5. System F System F is a simple language with an interesting type system. It allows quantification over types: implicational monadic second order logic. Λ A. (λ x : A. x) : ∀ A. A→A It is strongly normalising, so we can find a “value” for any program by applying reduction rules.

6. What does it mean to reduce?

7. System F - Extended Types {A,B,C} := 1| X | A→B | ∀ X.A | A+B | A*B X.A Terms {r,s,t} := x | f | () | λx:A.t | Λ X.t | r s | r A | inl(t,B) | inr(t,A) | (t,s) | in(t,A) | out(t,A) | split r as x1,x2 in s | case r of inl(x1) => s ; inr(x2) =>t Ctx {G} :=. | G,X | G,x:A D = a map from function constants to terms.

8. What have we done? Everything there is representable except unfolding. We can do sums, products and even least and greatest fixed points without extension – using a church encoding – but it's slow We've gained general recursion, lost normalisation. Cut evaluation into two peices!

9. We can't compare anymore We can still compare programs for syntactic equality, but it doesn't tell us anything about the unfolding behaviour. We want a behavioural model of the program. Let's see how things unfold

10. When is one thing like another? Morris contextual equivalence says that we want to know that C[e] = C[e'] for any context C. It's hard to quantify over contexts. Gordon tells us about another path – we can treat functional programs as a transition system. Equivalence becomes a question of bisimulation.

11. Two players, internal and external “A point to watch is to make a distinction between internal and external behaviour” - Plotkin We don't know what free variables are going to do except for what their type says. This is how supercompilation has always built process trees – nothing new. Our graph is built from a term t, using [t]

12. Transition System T = (S,A,:SxAxS)‏ A a set of actions – here determined by the language S a set of states – which are terms

13. Creating the Graph

14. Example

17. A Difference without a distinction Well known that we can distribute case – but we see it plainly here. Just compare edge labels and leaves to match. Where do these transitions come from?  They came from one-hole evaluation contexts – or atomic experiments that define the reduction semantics.  Case [] of... | Split [] as... | [] b

18. For Infinity

20. Arbitrary Bisimulation To show that a~b  Whenever (a,,a') in G1, then (b,,b') in G2 and a'~b'  Whenever (b,,b') in G2, then (a,,a') in G1,and a'~b'

21. Use Park's Principle We do this by coming up with a monotone relation, that we can use to replace ~, then we can easily show that it is a subset of ~ hence we can show ~ In practice this just means we have to be careful to have done something, before reusing our hypothesis. That is: assume a~b but make sure we have a transition before using it.

22. Composition of Graphs

23. Composition is Bisimilar [t] [s] ~ [t s] [t] T ~ [t T] We can go back and forth between splitting out separate graphs and combining into one.

24. Pending Questions Equivalence of process trees should give a contextual equivalence – we shouldn't need to show improvement, but I've yet to prove this. Do we need the improvement theorem?  In the f 0 = 42 example [Bird], we have equational rewriting going wrong, but we don't have a replacement of one normal form for an equivalent normal form. What fragments will we get normal forms for?

25. {- Also called min on natural numbers -} join :: CoTrue -> CoTrue -> CoTrue join T b = T join a T = T join (D a) (D b) = D (join a b)‏ ex :: (Nat -> CoTrue) -> NatStream -> CoTrue ex p (SCons x s) = D (join (p x) (ex p s))‏ {- Also called min on natural numbers -} join :: CoTrue -> CoTrue -> CoTrue join T b = T join a T = T join (D a) (D b) = D (join a b)‏ ex :: (Nat -> CoTrue) -> NatStream -> CoTrue ex p (SCons x s) = D (join (p x) (ex p s))‏ {- Also called min on natural numbers -} join :: CoTrue -> CoTrue -> CoTrue join T b = T join a T = T join (D a) (D b) = D (join a b)‏ ex :: (Nat -> CoTrue) -> NatStream -> CoTrue ex p (SCons x s) = D (join (p x) (ex p s))‏ data CoTrue = T | D CoTrue true = T false = D false eq Z Z = true eq (S x) (S y) = eq x y eq x y = false