## Polymorphic Types and System F

[Notes still to be added. Hope you paid attention during seminar.]

## Types in OCaml

OCaml has type inference: the system can often infer what the type of an expression must be, based on the type of other known expressions.

For instance, if we type

```
# let f x = x + 3;;
```

The system replies with

```
val f : int -> int = <fun>
```

Since `+`

is only defined on integers, it has type

```
# (+);;
- : int -> int -> int = <fun>
```

The parentheses are there to turn off the trick that allows the two
arguments of `+`

to surround it in infix (for linguists, SOV) argument
order. That is,

```
# 3 + 4 = (+) 3 4;;
- : bool = true
```

In general, tuples with one element are identical to their one element:

```
# (3) = 3;;
- : bool = true
```

though OCaml, like many systems, refuses to try to prove whether two functional objects may be identical:

```
# (f) = f;;
Exception: Invalid_argument "equal: functional value".
```

Oh well.

[Note: There is a limited way you can compare functions, using the
`==`

operator instead of the `=`

operator. Later when we discuss mutation,
we'll discuss the difference between these two equality operations.
Scheme has a similar pair, which they name `eq?`

and `equal?`

. In Python,
these are `is`

and `==`

respectively. It's unfortunate that OCaml uses `==`

for the opposite operation that Python and many other languages use it for. In any case, OCaml will accept `(f) == f`

even though it doesn't accept
`(f) = f`

. However, don't expect it to figure out in general when two functions
are equivalent. (That question is not Turing computable.)

```
# (f) == (fun x -> x + 3);;
- : bool = false
```

Here OCaml says (correctly) that the two functions don't stand in the `==`

relation, which basically means they're not represented in the same chunk of memory. However as the programmer can see, the functions are extensionally equivalent. The meaning of `==`

is rather weird.]

## Booleans in OCaml, and simple pattern matching

Where we would write `true 1 2`

in our pure lambda calculus and expect
it to evaluate to `1`

, in OCaml boolean types are not functions
(equivalently, they're functions that take zero arguments). Instead, selection is
accomplished as follows:

```
# if true then 1 else 2;;
- : int = 1
```

The types of the `then`

clause and of the `else`

clause must be the
same.

The `if`

construction can be re-expressed by means of the following
pattern-matching expression:

```
match <bool expression> with true -> <expression1> | false -> <expression2>
```

That is,

```
# match true with true -> 1 | false -> 2;;
- : int = 1
```

Compare with

```
# match 3 with 1 -> 1 | 2 -> 4 | 3 -> 9;;
- : int = 9
```

## Unit and thunks

All functions in OCaml take exactly one argument. Even this one:

```
# let f x y = x + y;;
# f 2 3;;
- : int = 5
```

Here's how to tell that `f`

has been curry'd:

```
# f 2;;
- : int -> int = <fun>
```

After we've given our `f`

one argument, it returns a function that is
still waiting for another argument.

There is a special type in OCaml called `unit`

. There is exactly one
object in this type, written `()`

. So

```
# ();;
- : unit = ()
```

Just as you can define functions that take constants for arguments

```
# let f 2 = 3;;
# f 2;;
- : int = 3;;
```

you can also define functions that take the unit as its argument, thus

```
# let f () = 3;;
val f : unit -> int = <fun>
```

Then the only argument you can possibly apply `f`

to that is of the
correct type is the unit:

```
# f ();;
- : int = 3
```

Now why would that be useful?

Let's have some fun: think of `rec`

as our `Y`

combinator. Then

```
# let rec f n = if (0 = n) then 1 else (n * (f (n - 1)));;
val f : int -> int = <fun>
# f 5;;
- : int = 120
```

We can't define a function that is exactly analogous to our ω.
We could try `let rec omega x = x x;;`

what happens?

[Note: if you want to learn more OCaml, you might come back here someday and try:

```
# let id x = x;;
val id : 'a -> 'a = <fun>
# let unwrap (`Wrap a) = a;;
val unwrap : [< `Wrap of 'a ] -> 'a = <fun>
# let omega ((`Wrap x) as y) = x y;;
val omega : [< `Wrap of [> `Wrap of 'a ] -> 'b as 'a ] -> 'b = <fun>
# unwrap (omega (`Wrap id)) == id;;
- : bool = true
# unwrap (omega (`Wrap omega));;
<Infinite loop, need to control-c to interrupt>
```

But we won't try to explain this now.]

Even if we can't (easily) express omega in OCaml, we can do this:

```
# let rec blackhole x = blackhole x;;
```

By the way, what's the type of this function?

If you then apply this `blackhole`

function to an argument,

```
# blackhole 3;;
```

the interpreter goes into an infinite loop, and you have to type control-c to break the loop.

Oh, one more thing: lambda expressions look like this:

```
# (fun x -> x);;
- : 'a -> 'a = <fun>
# (fun x -> x) true;;
- : bool = true
```

(But `(fun x -> x x)`

still won't work.)

You may also see this:

```
# (function x -> x);;
- : 'a -> 'a = <fun>
```

This works the same as `fun`

in simple cases like this, and slightly differently in more complex cases. If you learn more OCaml, you'll read about the difference between them.

We can try our usual tricks:

```
# (fun x -> true) blackhole;;
- : bool = true
```

OCaml declined to try to fully reduce the argument before applying the lambda function. Question: Why is that? Didn't we say that OCaml is a call-by-value/eager language?

Remember that `blackhole`

is a function too, so we can
reverse the order of the arguments:

```
# blackhole (fun x -> true);;
```

Infinite loop.

Now consider the following variations in behavior:

```
# let test = blackhole blackhole;;
<Infinite loop, need to control-c to interrupt>
# let test () = blackhole blackhole;;
val test : unit -> 'a = <fun>
# test;;
- : unit -> 'a = <fun>
# test ();;
<Infinite loop, need to control-c to interrupt>
```

We can use functions that take arguments of type `unit`

to control
execution. In Scheme parlance, functions on the `unit`

type are called
*thunks* (which I've always assumed was a blend of "think" and "chunk").

Question: why do thunks work? We know that `blackhole ()`

doesn't terminate, so why do expressions like:

```
let f = fun () -> blackhole ()
in true
```

terminate?

## Bottom type, divergence

Expressions that don't terminate all belong to the **bottom type**. This is a subtype of every other type. That is, anything of bottom type belongs to every other type as well. More advanced type systems have more examples of subtyping: for example, they might make `int`

a subtype of `real`

. But the core type system of OCaml doesn't have any general subtyping relations. (Neither does System F.) Just this one: that expressions of the bottom type also belong to every other type. It's as if every type definition in OCaml, even the built in ones, had an implicit extra clause:

```
type 'a option = None | Some of 'a;;
type 'a option = None | Some of 'a | bottom;;
```

Here are some exercises that may help better understand this. Figure out what is the type of each of the following:

```
fun x y -> y;;
fun x (y:int) -> y;;
fun x y : int -> y;;
let rec blackhole x = blackhole x in blackhole;;
let rec blackhole x = blackhole x in blackhole 1;;
let rec blackhole x = blackhole x in fun (y:int) -> blackhole y y y;;
let rec blackhole x = blackhole x in (blackhole 1) + 2;;
let rec blackhole x = blackhole x in (blackhole 1) || false;;
let rec blackhole x = blackhole x in 2 :: (blackhole 1);;
```

By the way, what's the type of this:

```
let rec blackhole (x:'a) : 'a = blackhole x in blackhole
```

Back to thunks: the reason you'd want to control evaluation with thunks is to
manipulate when "effects" happen. In a strongly normalizing system, like the
simply-typed lambda calculus or System F, there are no "effects." In Scheme and
OCaml, on the other hand, we can write programs that have effects. One sort of
effect is printing (think of the damn example at the start of term).
Another sort of effect is mutation, which we'll be looking at soon.
Continuations are yet another sort of effect. None of these are yet on the
table though. The only sort of effect we've got so far is *divergence* or
non-termination. So the only thing thunks are useful for yet is controlling
whether an expression that would diverge if we tried to fully evaluate it does
diverge. As we consider richer languages, thunks will become more useful.

## Towards Monads

This has now been moved to the start of week7.