Data is evidence

Recently I’ve been reading “Types and Programming Langauages” book by Benjamin C. Pierce. It’s a great introduction to theory behind type systems of both functional and object-oriented languages. In the first chapter there’s this really brilliant sentence that says what a type system does:

A type system can be regarded as calculating a kind of static approximation to the run-time behaviours of the terms in a program.

So if a type system is a static approximation of program’s behaviour at runtime a natural question to ask is: “how accurate this approximation can be?” Turns out it can be very accurate.

Let’s assume that we have following definition of natural numbers1:

data Nat : Set where
  zero : Nat
  suc  : Nat → Nat

First constructor – zero – says that zero is a natural number. Second – suc – says that successor of any natural number is also a natural number. This representation allows to encode 0 as zero, 1 as suc zero, 2 as suc (suc zero) and so on2. Let’s also define a type of booleans to represent logical true and false:

data Bool : Set where
  false : Bool
  true  : Bool

We can now define a operator that returns true if its arguments are in greater-equal relation and false if they are not:

__ : Nat → Nat → Bool
m     ≥ zero  = true
zero  ≥ suc n = false
suc m ≥ suc n = m ≥ n

This definition has three cases. First says that any natural number is greater than or equal to zero. Second says that zero is not greater than any successor. Final case says that two non-zero natural numbers are in ≥ relation if their predecessors are also in that relation. What if we replace false with true in our definition?

__ : Nat → Nat → Bool
m     ≥ zero  = true
zero  ≥ suc n = true
suc m ≥ suc n = m ≥ n

Well… nothing. We get a function that has nonsense semantics but other than that it is well-typed. The type system won’t catch this mistake. The reason for this is that our function returns a result but it doesn’t say why that result is true. And since doesn’t give us any evidence that result is correct there is no way of statically checking whether the implementation is correct or not.

But it turns out that we can do better using dependent types. We can write a comparison function that proves its result correct. Let’s forget our definition of and instead define datatype called :

data __ : Nat → Nat → Set where
  ge0 : {  y : Nat}         → y     ≥ zero
  geS : {x y : Nat} → x ≥ y → suc x ≥ suc y

This type has two Nat indices that parametrize it. For example: 5 ≥ 3 and 2 ≥ 0 are two distinct types. Notice that each constructor can only be used to construct values of a specific type: ge0 constructs a value that belongs to types like 0 ≥ 0, 1 ≥ 0, 3 ≥ 0 and so on. geS given a value of type x ≥ y constructs a value of type suc x ≥ suc y.

There are a few interesting properties of datatype. Notice that not only ge0 can construct value of types y ≥ 0, but it is also the only possible value of such types. In other words the only value of 0 ≥ 0, 1 ≥ 0 or 3 ≥ 0 is ge0. Types like 5 ≥ 3 also have only one value (in case of 5 ≥ 3 it is geS (geS (geS ge0))). That’s why we call a singleton type. Note also that there is no way to construct values of type 0 ≥ 3 or 5 ≥ 2 – there are no constructors that we could use to get a value of that type. We will thus say that datatype is a witness (or evidence): if we can construct a value for a given two indices then this value is a witness that relation represented by the datatype holds. For example geS (geS ge0)) is a witness that relations 2 ≥ 2 and 2 ≥ 5 hold but there is no way to provide evidence that 0 ≥ 1 holds. Notice that previous definition of function had three cases: one base case for true, one base case for false and one inductive case. The datatype has only two cases: one being equivalent of true and one inductive. Because the value of exists if and only if its two parameters are in ≥ relation there is no need to represent false explicitly.

We have a way to express proof that one value is greater than another. Let’s now construct a datatype that can say whether one value is greater than another and supply us with a proof of that fact:

data Order : Nat → Nat → Set where
  ge : {x : Nat} {y : Nat} → x ≥ y → Order x y
  le : {x : Nat} {y : Nat} → y ≥ x → Order x y

Order is indexed by two natural numbers. These numbers can be anything – there is no restriction on any of the constructors. We can construct values of Order using one of two constructors: ge and le. Constructing value of Order using ge constructor requires a value of type x ≥ y. In other words it requires a proof that x is greater than or equal to y. Constructing value of Order using le constructor requires the opposite proof – that y ≥ x. Order datatype is equivalent of Bool except that it is specialized to one particular relation instead of being a general statement of truth or false. It also carries a proof of the fact that it states.

Now we can write a function that compares two natural numbers and returns a result that says whether first number is greater than or equal to the second one3:

order : (x : Nat)(y : Nat) → Order x y
order x       zero    = ge ge0
order zero    (suc b) = le ge0
order (suc a) (suc b) with order a b
order (suc a) (suc b) | ge a≥b = ge (geS a≥b)
order (suc a) (suc b) | le b≥a = le (geS b≥a)

In this implementation ge plays the role of true and le plays the role of false. But if we try to replace le with ge the way we previously replaced false with true the result will not be well-typed:

order : (x : Nat)(y : Nat) → Order x y
order x       zero    = ge ge0
order zero    (suc b) = ge ge0 -- TYPE ERROR
order (suc a) (suc b) with order a b
order (suc a) (suc b) | ge a≥b = ge (geS a≥b)
order (suc a) (suc b) | le b≥a = le (geS b≥a)

Why? It is a direct result of the definitions that we used. In the second equation of order, x is zero and y is suc b. To construct a value of Order x y using ge constructor we must provide a proof that x ≥ y. In this case we would have to prove that zero ≥ suc b, but as discussed previously there is no constructor of that could construct value of this type. Thus the whole expression is ill-typed and the incorrectness of our definition is caught at compile time.

Summary

The idea that types can represent logical propositions and values can be viewed as proofs of these propositions is not new – it is known as Curry-Howard correspondence (or isomorphism) and I bet many of you have heard that name. Example presented here is taken from “Why Dependent Types Matter”. See this recent post for a few more words about this paper.

  1. All code in this post is in Agda. []
  2. For the sake of readability I will write Nats as numerals, not as applications of suc and zero. So remember that whenever I write 2 I mean suc (suc zero) []
  3. Note that in Agda a≥b is a valid identifier, not an application of []

2 Responses to “Data is evidence”

  1. Francesco says:

    Very interesting article. Even thought it’s written in Agda (which I know nothing about), this is the clearest Curry-Howard isomorphism exemplification I have read to date

  2. Ben says:

    Nice article! One nitpick: I don’t think it’s quite right to say that (for instance) ge0 is the only value of type 1 >= 0. All you can really say is that every value of that type is equal to qe0 — which isn’t precisely the same thing. At least not if you use {-# OPTION –without-K -#} …

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