# Currying and Staging

By Brandon Wu, June 2020

Suppose that we are interested in writing a function that adds two numbers. This is fairly simple - this is not a new concept to us.

fun add (x, y) = x + y


Then this function should clearly have type int * int -> int. We also know that this notation is really just syntactic sugar for the following:

val add = fn (x, y) => x + y


It binds the lambda expression that takes in a tuple of two integers and adds them together to the identifier of add. Yet with our knowledge of expressions and values, it is not too outlandish to write the following instead:

fun addCurry x = fn y => x + y


What might be the type of this function? Well, we know that addCurry takes in a value x, which should be an int, since it is summed with y. It then returns a lambda expression that takes in that same y, and returns the sum, which is an int. It seems to us that the type should be int -> (int -> int). This is an example of a curried function, and one of the first examples we will see of a higher-order function.

[Higher-Order Functions] A higher-order function is a function that takes in other functions as input, or returns a function as output.

[Currying] Named after mathematician/logician Haskell Brooks Curry, currying is the act of transforming a function that takes multiple arguments into a function that returns a function that takes the remaining arguments. Intuitively, it separates the arguments into a series of function applications, instead of all at once. We may refer to a general higher-order function that returns a function as a curried function.

An important note is that in the type int -> (int -> int), the parentheses are unnecessary. This is because type arrows are right-associative, in the same way that :: is. This means that there is already an implicit parentheses in the type int -> int -> int - the function simply takes in an integer and returns a function from int -> int. This is thus a separate type than (int -> int) -> int, which is a function that takes in a function from int -> int and returns an integer.

Note that in the curried example of addCurry we wrote above, this is really syntactic sugar for the following:

val addCurry = fn x => fn y => x + y


Not being ones to skimp on the syntactic sugar (which perhaps spells danger for our syntactic blood sugar levels), we can take this one step further. We can write the exact same declaration in a more concise way, using the form:

fun addCurry x y = x + y


This thus will curry our arguments for us, when we separate them by a space.

Note that our implementations of addCurry and add are not extensionally equivalent - for the simple reason that they do not even have the same type! They do, however, in a sense correspond, in that they seem to do the same thing - that is, add numbers together. The manner in which they do so is entirely disparate, however.

It is important to note that currying our functions gives us a notion of partial application, where we can give a curried function only some of its "arguments". This lends us to further specialization and modularity based on the use case and amount of information available. This is discussed more in the coming section.

## Revisiting Extensional Equivalence

In previous chapters, we have explored the idea of extensional equivalence, and constructed a definition for extensional equivalence that covered two cases - the function case and the non-function case.

We seemed to agree on a meaning that said that, for non-function values, two values are extensionally equivalent if they are the same value, which is an perhaps an ill-justified definition that may leave a bad taste in one's mouth, but ultimately boils down to our intuitive notion that, yes, some values are just the same and we can't really do much more than question that. For instance, we can see that (1, 2, "hi") and (1, 2, "hi") are the "same", and neither are the same as (2, 1, "hello"). For functions, however, we decided on a slightly more appeasing definition that defined a function by its input-output behavior. We restate the definition below:

[Extensional Equivalence (Functions)] We say two expressions e : t1 -> t2 and e' : t1 -> t2 for some types t1 and t2 are extensionally equivalent if for all values x : t1, e x $$\cong$$e' x.

It is our hope that we are now in a place to properly appreciate this definition. For functions that have type int -> int, this is a fairly straightforward definition - these functions are extensionally equivalent if, for every integer that we give them, they return the same int. However, what about curried functions? Our definition, in light of this new concept, is that curried functions are extensionally equivalent if the functions that they return are extensionally equivalent.

No matter how deeply nested this currying takes place, this definition will suffice. Types must be finite, so we must eventually reach a point where we can say that values are "the same" (excluding the existence of non-equality types, perhaps). We can see now that this idea of extensional equivalence is elegantly compatible with the existence of curried functions, being a recursive definition much in the same way that the datatypes that we declare or the functions that we write are.

## Staging

With curried functions, we can have much more deliberate control over when a function does evaluation, particularly with respect to the inputs that it receives.

Consider an analogy. Suppose you have math homework to do, but you left your calculator at home. A more lazy-minded student might procrastinate, thinking that they would only start once they got home, but a more pragmatically-minded individual might simply start on the problems that don't require a calculator. The idea of staging is that we can reap efficiency benefits for certain problems when facing a scarcity of information, by simply doing computations that require the arguments that are at hand first. We thus make a distinction between functions that must have all of their arguments to do useful work, and those who do not.

For instance, take the addition function.

fun add (x : int, y : int) : int = x + y


This is not a function that we would categorize as being able to do "useful work" with a single one of its arguments. Even if we were to curry add, with only one int it can't really do anything but simply wait for the second argument. In this case, the efficiency benefits are marginal at best. The computations are somewhat "dependent" - we need access to both arguments in order to do anything meaningful.

Consider a more contrived example:

(* contrived : int -> int -> int *)
fun contrived x y =
let
val z = horrible_computation x (* this takes 3 years *)
in
y + z
end


The function contrived takes in two arguments x and y. It then performs some transformation on x using the function horrible_computation (which takes 3 years to run, unfortunately), and then adds y to the result of that transformation z.

Suppose that we are interested in computing the results of contrived 4 2 and contrived 4 5, for no reason other than because we can. Then, clearly evaluation of those two expressions will take 3 years each (per horrible_computation's horrible computational nature) - totalling up to six years! This is far too long, and we want to do better.

One thing that we note is that almost all of the work that we expended in computing contrived 4 2 and contrived 4 5 was in evaluating horrible_computation 4. This computation took us 3 years, but we repeated it twice! In both of queries we made, we had to compute the exact same thing, which led to major inefficiencies. The rest of the work of contrived was negligible compared to the overhead of horrible_computation. It seems that we should be able to achieve better results.

(* contrivedStaged : int -> int -> int *)
fun contrivedStaged x =
let
val z = horrible_computation x (* this still takes 3 years *)
in
fn y => y + z
end


Now, we have staged contrived. contrivedStaged still has the same type as contrived, but it behaves slightly differently. It is not too difficult to see that contrived is extensionally equivalent to contrivedStaged, but we have made a slightly more optimal change with regards to SML's semantics.

Now, instead of waiting for the second argument y to begin executing horrible_computation x, contrivedStaged does so immediately after receiving x. This is clearly better - there was no point to wait for y in the first place, since horrible_computation does not depend on it. So now we can execute the following code fragment:

val intermediate = contrivedStaged 4
val ans1 = intermediate 2
val ans2 = intermediate 5
(* takes 3 years in total *)


We can do this because contrivedStaged 4 computes the result of horrible_computation 4, and then stores the result in the closure of the function that it returns. This means that, in the scope of intermediate, it contains the answer that was common to both of the expressions we wrote earlier. Now, we can execute the step of y + z (which is nearly instantaneous), cutting our runtime in half. Now, we can obtain the result of contrived 4 2 and contrived 4 5 in only 3 years (though to evaluate both of those expressions themselves would still take 6 years!).

It is important to note that currying is not the same thing as staging. contrived was curried, but not staged optimally - we made a change that, even though it had the same type, let us structure our queries in a more optimal manner. This is an important idea with many applications, such as when building up a data structure to make queries to, or in graphics when a lot of work must first be done to preprocess the given data.