Difference between Recursion and Iteration

A program is called recursive when an entity calls itself. A program is call iterative when there is a loop (or repetition).

Example: Program to find the factorial of a number

C++

filter_none

edit
close

play_arrow

link
brightness_4
code

// C++ program to find factorial of given number
#include<bits/stdc++.h>
using namespace std;
  
// ----- Recursion -----
// method to find factorial of given number
int factorialUsingRecursion(int n)
{
    if (n == 0)
        return 1;
  
    // recursion call
    return n * factorialUsingRecursion(n - 1);
}
  
// ----- Iteration -----
// Method to find the factorial of a given number
int factorialUsingIteration(int n)
{
    int res = 1, i;
  
    // using iteration
    for (i = 2; i <= n; i++)
        res *= i;
  
    return res;
}
  
// Driver method
int main()
{
    int num = 5;
    cout << "Factorial of " << num << 
            " using Recursion is: " <<
            factorialUsingRecursion(5) << endl;
  
    cout << "Factorial of " << num <<
            " using Iteration is: " << 
            factorialUsingIteration(5);
  
    return 0;
}
  
// This code is contributed by mits

chevron_right


Java

filter_none

edit
close

play_arrow

link
brightness_4
code

// Java program to find factorial of given number
class GFG {
  
    // ----- Recursion -----
    // method to find factorial of given number
    static int factorialUsingRecursion(int n)
    {
        if (n == 0)
            return 1;
  
        // recursion call
        return n * factorialUsingRecursion(n - 1);
    }
  
    // ----- Iteration -----
    // Method to find the factorial of a given number
    static int factorialUsingIteration(int n)
    {
        int res = 1, i;
  
        // using iteration
        for (i = 2; i <= n; i++)
            res *= i;
  
        return res;
    }
  
    // Driver method
    public static void main(String[] args)
    {
        int num = 5;
        System.out.println("Factorial of " + num
                           + " using Recursion is: "
                           + factorialUsingRecursion(5));
  
        System.out.println("Factorial of " + num
                           + " using Iteration is: "
                           + factorialUsingIteration(5));
    }
}

chevron_right


Python3

filter_none

edit
close

play_arrow

link
brightness_4
code

# Python3 program to find factorial of given number
  
# ----- Recursion -----
# method to find factorial of given number
def factorialUsingRecursion(n):
    if (n == 0):
        return 1;
  
    # recursion call
    return n * factorialUsingRecursion(n - 1);
  
# ----- Iteration -----
# Method to find the factorial of a given number
def factorialUsingIteration(n):
    res = 1;
  
    # using iteration
    for i in range(2, n + 1):
        res *= i;
  
    return res;
  
# Driver method
num = 5;
print("Factorial of",num,"using Recursion is:",
                    factorialUsingRecursion(5));
  
print("Factorial of",num,"using Iteration is:",
                    factorialUsingIteration(5));
      
# This code is contributed by mits

chevron_right


C#

filter_none

edit
close

play_arrow

link
brightness_4
code

// C# program to find factorial of 
// given number
using System;
  
class GFG
{
  
    // ----- Recursion -----
    // method to find factorial of 
    // given number
    static int factorialUsingRecursion(int n)
    {
        if (n == 0)
            return 1;
  
        // recursion call
        return n * factorialUsingRecursion(n - 1);
    }
  
    // ----- Iteration -----
    // Method to find the factorial of
    // a given number
    static int factorialUsingIteration(int n)
    {
        int res = 1, i;
  
        // using iteration
        for (i = 2; i <= n; i++)
            res *= i;
  
        return res;
    }
  
    // Driver Code
    public static void Main(String[] args)
    {
        int num = 5;
        Console.WriteLine("Factorial of " + num + 
                          " using Recursion is: "
                          factorialUsingRecursion(5));
  
        Console.WriteLine("Factorial of " + num + 
                          " using Iteration is: "
                          factorialUsingIteration(5));
    }
}
  
// This code has been contributed by Rajput-Ji 

chevron_right


PHP

filter_none

edit
close

play_arrow

link
brightness_4
code

<?php
// PHP program to find factorial of given number
  
    // ----- Recursion -----
    // method to find factorial of given number
    function factorialUsingRecursion($n)
    {
        if ($n == 0)
            return 1;
  
        // recursion call
        return $n * factorialUsingRecursion($n - 1);
    }
  
    // ----- Iteration -----
    // Method to find the factorial of a given number
    function factorialUsingIteration($n)
    {
        $res = 1;
  
        // using iteration
        for ($i = 2; $i <= $n; $i++)
            $res *= $i;
  
        return $res;
    }
  
    // Driver method
        $num = 5;
        print("Factorial of ".$num." using Recursion is: ".
                            factorialUsingRecursion(5)."\n");
  
        print("Factorial of ".$num." using Iteration is: ".
                            factorialUsingIteration(5)."\n");
      
// This code is contributed by mits
?>

chevron_right


Output:



Factorial of 5 using Recursion is: 120
Factorial of 5 using Iteration is: 120

Below are the detailed example to illustrate the difference between the two:

  1. Time Complexity: Finding the Time complexity of Recursion is more difficult than that of Iteration.
    • Recursion: Time complexity of recursion can be found by finding the value of the nth recursive call in terms of the previous calls. Thus, finding the destination case in terms of the base case, and solving in terms of the base case gives us an idea of the time complexity of recursive equations. Please see Solving Recurrences for more details.
    • Iteration: Time complexity of iteration can be found by finding the number of cycles being repeated inside the loop.
  2. Usage: Usage of either of these techniques is a trade-off between time complexity and size of code. If time complexity is the point of focus, and number of recursive calls would be large, it is better to use iteration. However, if time complexity is not an issue and shortness of code is, recursion would be the way to go.
    • Recursion: Recursion involves calling the same function again, and hence, has a very small length of code. However, as we saw in the analysis, the time complexity of recursion can get to be exponential when there are a considerable number of recursive calls. Hence, usage of recursion is advantageous in shorter code, but higher time complexity.
    • Iteration: Iteration is repetition of a block of code. This involves a larger size of code, but the time complexity is generally lesser than it is for recursion.
  3. Overhead: Recursion has a large amount of Overhead as compared to Iteration.
    • Recursion: Recursion has the overhead of repeated function calls, that is due to repetitive calling of the same function, the time complexity of the code increases manifold.
    • Iteration: Iteration does not involve any such overhead.
  4. Infinite Repetition: Infinite Repetition in recursion can lead to CPU crash but in iteration, it will stop when memory is exhausted.
    • Recursion: In Recursion, Infinite recursive calls may occur due to some mistake in specifying the base condition, which on never becoming false, keeps calling the function, which may lead to system CPU crash.
    • Iteration: Infinite iteration due to mistake in iterator assignment or increment, or in the terminating condition, will lead to infinite loops, which may or may not lead to system errors, but will surely stop program execution any further.

 

Property Recursion Iteration
Definition Function calls itself. A set of instructions repeatedly executed.
Application For functions. For loops.
Termination Through base case, where there will be no function call. When the termination condition for the iterator ceases to be satisfied.
Usage Used when code size needs to be small, and time complexity is not an issue. Used when time complexity needs to be balanced against an expanded code size.
Code Size Smaller code size Larger Code Size.
Time Complexity Very high(generally exponential) time complexity. Relatively lower time complexity(generally polynomial-logarithmic).

 



My Personal Notes arrow_drop_up

Front and Back End Web Developer Android Developer Python and C++ Coder Networking Geek

If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.

Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.



Improved By : Rajput-Ji, Mithun Kumar