This is my conversation with my custom GPT. Beyond this point, my questions are in blockquotes, and the GPT's responses are in normal text.
Can you help me explain to my friend how higher-order functions can be replaced with parameterized modules? Here's the rub: I don't want you to do it with OBJ, I want you to show how to do it with parameterized modules in OCaml. FYI - He's an F# programmer, so you don't have to explain things like higher-order functions.
Here's the paper: https://cseweb.ucsd.edu/~goguen/pps/utyop.pdf
Hey Friend,
Let’s talk about how you can replace higher-order functions with parameterized modules in OCaml. Since you're already familiar with higher-order functions, I'll dive straight into how this can be done with modules.
In OCaml, parameterized modules (also known as functors) allow us to pass modules as arguments to other modules, similar to how you'd pass functions as arguments in higher-order functions. This technique provides a way to achieve modularity and code reuse, just like higher-order functions but with a twist that fits well with OCaml’s type system.
Let's break down the code piece by piece.
First, we define a module type, MONOID
, which acts like an interface. This is where you declare the operations that any module implementing this type should provide.
module type MONOID =
sig
type t
val neutral : t
val combine : t -> t -> t
end
Here, t
is the type of the elements in the monoid, neutral
is the identity element, and combine
is the operation that combines two elements.
Next, we define a parameterized module Iter
, which takes a module M
that matches the MONOID
signature.
module Iter (M: MONOID) =
struct
type e = M.t
let rec iter = function
| [] -> M.neutral
| x :: xs -> M.combine x (iter xs)
end
This module Iter
provides a function iter
that folds a list using the combine
function from the M
module. It’s like a general-purpose fold that can work with any monoid.
Now, let’s implement a concrete monoid. Here’s a simple one for summing integers:
module Sum : MONOID with type t = int =
struct
type t = int
let neutral = 0
let combine = (+)
end
This Sum
module defines the type t
as int
, the neutral
element as 0
, and the combine
function as the addition operator.
Finally, we apply the Iter
functor to the Sum
module to get a specialized version of the iter
function that sums a list of integers:
module SumIter = Iter(Sum)
Now, SumIter
is a module with an iter
function that sums up a list of integers using the monoid's combine
and neutral
.
Here’s how you can use it:
let () =
let r = SumIter.iter [1;2;3;4;5] in
Js.log(r)
This code will log the sum of [1;2;3;4;5]
to the console.
The key idea is that instead of passing functions directly (like you would with higher-order functions), you pass around entire modules. This approach is more type-safe and modular in OCaml because the module system ensures that all necessary operations (like combine
and neutral
) are provided by the module you pass in.
It’s a powerful technique when you want to enforce certain structures or operations across different types, making your code both flexible and safe.
If you want to play around with the code and see how it gets compiled into JavaScript: