Higher-order function

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In mathematics and computer science, a higher-order function (also functional, functional form or functor) is a function that does at least one of the following:

All other functions are first-order functions. In mathematics higher-order functions are also termed operators or functionals. The differential operator in calculus is a common example, since it maps a function to its derivative, also a function.

In the untyped lambda calculus, all functions are higher-order; in a typed lambda calculus, from which most functional programming languages are derived, higher-order functions that take one function as argument are values with types of the form .

General examples[edit]

  • map function, found in many functional programming languages, is one example of a higher-order function. It takes as arguments a function f and a list of elements, and as the result, returns a new list with f applied to each element from the list.
  • Sorting functions, which take a comparison function as a parameter, allowing the programmer to separate the sorting algorithm from the comparisons of the items being sorted. The C standard function qsort is an example of this.
  • fold
  • Function composition
  • Integration
  • Callback
  • Tree traversal

Support in programming languages[edit]

Direct support[edit]

The examples are not intended to compare and contrast programming languages, but to serve as examples of higher-order function syntax

In the following examples, the higher-order function twice takes a function, and applies the function to some value twice. If twice has to be applied several times for the same f it preferably should return a function rather than a value. This is in line with the "don't repeat yourself" principle.

Python 2[edit]

>>> def twice(f):
...     return lambda x: f(f(x))

>>> def f(x):
...     return x + 3

>>> g = twice(f)
>>> print g(7)


{$mode objfpc}
type fun = function(x:integer):integer;

function f(x:integer):integer;
	f:= x+3;

function g( func:fun; x:integer):integer;
        g:= func(x)*func(x);

     write(g(@f, 7));


let twice f = f >> f

let f = (+) 3

twice f 7 |> printf "%A" // 13


Func<Func<int, int>, int, int> twice = (func, i) => func(func(i));
Func<int, int> f = x => x + 3;

Console.WriteLine(twice(f, 7));


twice :: (a -> a) -> (a -> a)
twice f = f . f

f :: Num a => a -> a
f = subtract 3

main :: IO ()
main = print (twice f 7) -- 1


(defn twice [function x]
  (function (function x)))

(twice #(+ % 3) 7) ;13

In Clojure, "#" starts a lambda expression, and "%" refers to the next function argument.


(define (add x y) (+ x y))
(define (f x)
  (lambda (y) (+ x y)))
(display ((f 3) 7))
(display (add 3 7))

In this Scheme example, the higher-order function (f x) is used to implement currying. It takes a single argument and returns a function. The evaluation of the expression ((f 3) 7) first returns a function after evaluating (f 3). The returned function is (lambda (y) (+ 3 y)). Then, it evaluates the returned function with 7 as the argument, returning 10. This is equivalent to the expression (add 3 7), since (f x) is equivalent to the curried form of (add x y).


or_else([], _) -> false;
or_else([F | Fs], X) -> or_else(Fs, X, F(X)).

or_else(Fs, X, false) -> or_else(Fs, X);
or_else(Fs, _, {false, Y}) -> or_else(Fs, Y);
or_else(_, _, R) -> R.

or_else([fun erlang:is_integer/1, fun erlang:is_atom/1, fun erlang:is_list/1],3.23).

In this Erlang example, the higher-order function or_else/2 takes a list of functions (Fs) and argument (X). It evaluates the function F with the argument X as argument. If the function F returns false then the next function in Fs will be evaluated. If the function F returns {false,Y} then the next function in Fs with argument Y will be evaluated. If the function F returns R the higher-order function or_else/2 will return R. Note that X, Y, and R can be functions. The example returns false.


In Elixir, you can mix module definitions and anonymous functions

defmodule Hop do
    def twice(f, v) do

add3 = fn(v) -> 3 + v end

IO.puts Hop.twice(add3, 7) #13

Alternatively, we can also compose using pure anonymous functions.

twice = fn(f, v) -> f.(f.(v)) end
add3 = fn(v) -> 3 + v end

IO.puts twice.(add3, 7) #13


const twice = (f, v) => f(f(v));
const add3 = v => v + 3;

twice(add3, 7); // 13


func twice(f func(int) int, v int) int {
	return f(f(v))

func main() {
	f := func(v int) int {
		return v + 3
	twice(f, 7) // returns 13

Notice a function literal can be defined either with an identifier (twice) or anonymously (assigned to variable f). Run full program on Go Playground!


def twice(f:Int=>Int) = f compose f

twice(_+3)(7) // 13

Java (1.8+)[edit]

Function<Function<Integer, Integer>, Function<Integer, Integer>> twice = f -> f.andThen(f);
twice.apply(x -> x + 3).apply(7); // 13


fun <T> twice(f: (T)->T): (T)->T = {f(f(it))}
fun f(x:Int) = x + 3
println(twice(::f)(7)) // 13


local twice = function(f,v)
    return f(f(v))

local f = function(v)
    return v + 3

print(twice(f,7)) -- 13


func twice(_ f: @escaping (Int) -> Int) -> (Int) -> Int { return { f(f($0)) } }

func f(_ arg: Int) -> Int { return arg + 3 }

let g = twice(f)
print(g(7)) // 13


// Take function f(x), return function f(f(x))
fn twice<A, F>(function: F) -> Box<Fn(A) -> A> 
    where F: 'static + Fn(A) -> A
    Box::new(move |a| function(function(a)))

// Return x + 3
fn f(x: i32) -> i32 {
    x + 3

fn main() {
    let g = twice(f);
    println!("{}", g(7));


// Generic lambdas provided by C++14.
#include <iostream>

auto twice = [](auto f, int v)
    return f(f(v));
auto f = [](int i)
    return i + 3;
int main()
    std::cout << twice(f, 7) << std::endl;

// Or, use std::function in C++11
#include <iostream>
#include <functional>

auto twice = [](const std::function<int(int)>& f, int v)
    return f(f(v));
auto f = [](int i)
    return i + 3;
int main()
    std::cout << twice(f, 7) << std::endl;


import std.stdio : writeln;

alias twice = (f, i) => f(f(i));
alias f = (int i) => i + 3;

void main()
    writeln(twice(f, 7));

ColdFusion Markup Language (CFML)[edit]

twice = function(f, v) {
    return f(f(v));

f = function(v) {
    return v + 3;

writeOutput(twice(f, 7)); // 13


$twice = function($f, $v) {
    return $f($f($v));

$f = function($v) {
    return $v + 3;

echo($twice($f, 7)); // 13


twice <- function(func) {
  return(function(x) {

f <- function(x) {
  return(x + 3)

g <- twice(f)

> print(g(7))
[1] 13

Perl 6[edit]

sub twice(Callable:D $c) {
    return sub { $c($c($^x)) };

sub f(Int:D $x) {
    return $x + 3;

my $g = twice(&f);

say $g(7); #OUTPUT: 13

In Perl 6, all code objects are closures and therefore can reference inner "lexical" variables from an outer scope because the lexical variable is "closed" inside of the function. Perl 6 also supports "pointy block" syntax for lambda expressions which can be assigned to a variable or invoked anonymously.


set twice {{f v} {apply $f [apply $f $v]}}
set f {{v} {return [expr $v + 3]}}

# result: 13
puts [apply $twice $f 7]

Tcl uses apply command to apply an anonymous function (since 8.6).


The XACML standard defines higher-order functions in the standard to apply a function to multiple values of attribute bags.

rule allowEntry{
    condition anyOfAny(function[stringEqual], citizenships, allowedCitizenships)

The list of higher-order functions is can be found here.


Function pointers[edit]

Function pointers in languages such as C and C++ allow programmers to pass around references to functions. The following C code computes an approximation of the integral of an arbitrary function:

#include <stdio.h>

double square(double x)
    return x * x;

double cube(double x)
    return x * x * x;

/* Compute the integral of f() within the interval [a,b] */
double integral(double f(double x), double a, double b, int n)
    int i;
    double sum = 0;
    double dt = (b - a) / n;
    for (i = 0;  i < n;  ++i) {
        sum += f(a + (i + 0.5) * dt);
    return sum * dt;

int main()
    printf("%g\n", integral(square, 0, 1, 100));
    printf("%g\n", integral(cube, 0, 1, 100));
    return 0;

The qsort function from the C standard library uses a function pointer to emulate the behavior of a higher-order function.


Macros can also be used to achieve some of the effects of higher order functions. However, macros cannot easily avoid the problem of variable capture; they may also result in large amounts of duplicated code, which can be more difficult for a compiler to optimize. Macros are generally not strongly typed, although they may produce strongly typed code.

Dynamic code evaluation[edit]

In other imperative programming languages, it is possible to achieve some of the same algorithmic results as are obtained via higher-order functions by dynamically executing code (sometimes called Eval or Execute operations) in the scope of evaluation. There can be significant drawbacks to this approach:

  • The argument code to be executed is usually not statically typed; these languages generally rely on dynamic typing to determine the well-formedness and safety of the code to be executed.
  • The argument is usually provided as a string, the value of which may not be known until run-time. This string must either be compiled during program execution (using just-in-time compilation) or evaluated by interpretation, causing some added overhead at run-time, and usually generating less efficient code.


In object-oriented programming languages that do not support higher-order functions, objects can be an effective substitute. An object's methods act in essence like functions, and a method may accept objects as parameters and produce objects as return values. Objects often carry added run-time overhead compared to pure functions, however, and added boilerplate code for defining and instantiating an object and its method(s). Languages that permit stack-based (versus heap-based) objects or structs can provide more flexibility with this method.

An example of using a simple stack based record in Free Pascal with a function that returns a function:

program example;

  int = integer;
  Txy = record x, y: int; end;
  Tf = function (xy: Txy): int;
function f(xy: Txy): int; 
  Result := xy.y + xy.x; 

function g(func: Tf): Tf; 
  result := func; 

  a: Tf;
  xy: Txy = (x: 3; y: 7);

  a := g(@f);     // return a function to "a"
  writeln(a(xy)); // prints 10

The function a() takes a Txy record as input and returns the integer value of the sum of the record's x and y fields (3 + 7).


Defunctionalization can be used to implement higher-order functions in languages that lack first-class functions:

// Defunctionalized function data structures
template<typename T> struct Add { T value; };
template<typename T> struct DivBy { T value; };
template<typename F, typename G> struct Composition { F f; G g; };

// Defunctionalized function application implementations
template<typename F, typename G, typename X>
auto apply(Composition<F, G> f, X arg) {
    return apply(f.f, apply(f.g, arg));

template<typename T, typename X>
auto apply(Add<T> f, X arg) {
    return arg  + f.value;

template<typename T, typename X>
auto apply(DivBy<T> f, X arg) {
    return arg / f.value;

// Higher-order compose function
template<typename F, typename G>
Composition<F, G> compose(F f, G g) {
    return Composition<F, G> {f, g};

int main(int argc, const char* argv[]) {
    auto f = compose(DivBy<float>{ 2.0f }, Add<int>{ 5 });
    apply(f, 3); // 4.0f
    apply(f, 9); // 7.0f
    return 0;

In this case, different types are used to trigger different functions via function overloading. The overloaded function in this example has the signature auto apply.

See also[edit]