Merge Sort – Data Structure and Algorithms Tutorials

Merge sort is a sorting algorithm that follows the divide-and-conquer approach. It works by recursively dividing the input array into smaller subarrays and sorting those subarrays then merging them back together to obtain the sorted array.

In simple terms, we can say that the process of merge sort is to divide the array into two halves, sort each half, and then merge the sorted halves back together. This process is repeated until the entire array is sorted.

Merge Sort Algorithm

How does Merge Sort work?

Merge sort is a popular sorting algorithm known for its efficiency and stability. It follows the divide-and-conquer approach to sort a given array of elements.

Here’s a step-by-step explanation of how merge sort works:

1. Divide: Divide the list or array recursively into two halves until it can no more be divided.
2. Conquer: Each subarray is sorted individually using the merge sort algorithm.
3. Merge: The sorted subarrays are merged back together in sorted order. The process continues until all elements from both subarrays have been merged.

Illustration of Merge Sort:

Let’s sort the array or list [38, 27, 43, 10] using Merge Sort

Let’s look at the working of above example:

Divide:

• [38, 27, 43, 10] is divided into [38, 27] and [43, 10].
• [38, 27] is divided into [38] and [27].
• [43, 10] is divided into [43] and [10].

Conquer:

• [38] is already sorted.
• [27] is already sorted.
• [43] is already sorted.
• [10] is already sorted.

Merge:

• Merge [38] and [27] to get [27, 38].
• Merge [43] and [10] to get [10,43].
• Merge [27, 38] and [10,43] to get the final sorted list [10, 27, 38, 43]

Therefore, the sorted list is [10, 27, 38, 43].

Implementation of Merge Sort:

// C++ program for Merge Sort
#include <bits/stdc++.h>
using namespace std;

// Merges two subarrays of array[].
// First subarray is arr[begin..mid]
// Second subarray is arr[mid+1..end]
void merge(int array[], int const left, int const mid,
           int const right)
{
    int const subArrayOne = mid - left + 1;
    int const subArrayTwo = right - mid;

    // Create temp arrays
    auto *leftArray = new int[subArrayOne],
         *rightArray = new int[subArrayTwo];

    // Copy data to temp arrays leftArray[] and rightArray[]
    for (auto i = 0; i < subArrayOne; i++)
        leftArray[i] = array[left + i];
    for (auto j = 0; j < subArrayTwo; j++)
        rightArray[j] = array[mid + 1 + j];

    auto indexOfSubArrayOne = 0, indexOfSubArrayTwo = 0;
    int indexOfMergedArray = left;

    // Merge the temp arrays back into array[left..right]
    while (indexOfSubArrayOne < subArrayOne
           && indexOfSubArrayTwo < subArrayTwo) {
        if (leftArray[indexOfSubArrayOne]
            <= rightArray[indexOfSubArrayTwo]) {
            array[indexOfMergedArray]
                = leftArray[indexOfSubArrayOne];
            indexOfSubArrayOne++;
        }
        else {
            array[indexOfMergedArray]
                = rightArray[indexOfSubArrayTwo];
            indexOfSubArrayTwo++;
        }
        indexOfMergedArray++;
    }

    // Copy the remaining elements of
    // left[], if there are any
    while (indexOfSubArrayOne < subArrayOne) {
        array[indexOfMergedArray]
            = leftArray[indexOfSubArrayOne];
        indexOfSubArrayOne++;
        indexOfMergedArray++;
    }

    // Copy the remaining elements of
    // right[], if there are any
    while (indexOfSubArrayTwo < subArrayTwo) {
        array[indexOfMergedArray]
            = rightArray[indexOfSubArrayTwo];
        indexOfSubArrayTwo++;
        indexOfMergedArray++;
    }
    delete[] leftArray;
    delete[] rightArray;
}

// begin is for left index and end is right index
// of the sub-array of arr to be sorted
void mergeSort(int array[], int const begin, int const end)
{
    if (begin >= end)
        return;

    int mid = begin + (end - begin) / 2;
    mergeSort(array, begin, mid);
    mergeSort(array, mid + 1, end);
    merge(array, begin, mid, end);
}

// UTILITY FUNCTIONS
// Function to print an array
void printArray(int A[], int size)
{
    for (int i = 0; i < size; i++)
        cout << A[i] << " ";
    cout << endl;
}

// Driver code
int main()
{
    int arr[] = { 12, 11, 13, 5, 6, 7 };
    int arr_size = sizeof(arr) / sizeof(arr[0]);

    cout << "Given array is \n";
    printArray(arr, arr_size);

    mergeSort(arr, 0, arr_size - 1);

    cout << "\nSorted array is \n";
    printArray(arr, arr_size);
    return 0;
}

// This code is contributed by Mayank Tyagi
// This code was revised by Joshua Estes

// C program for Merge Sort
#include <stdio.h>
#include <stdlib.h>

// Merges two subarrays of arr[].
// First subarray is arr[l..m]
// Second subarray is arr[m+1..r]
void merge(int arr[], int l, int m, int r)
{
    int i, j, k;
    int n1 = m - l + 1;
    int n2 = r - m;

    // Create temp arrays
    int L[n1], R[n2];

    // Copy data to temp arrays L[] and R[]
    for (i = 0; i < n1; i++)
        L[i] = arr[l + i];
    for (j = 0; j < n2; j++)
        R[j] = arr[m + 1 + j];

    // Merge the temp arrays back into arr[l..r
    i = 0;
    j = 0;
    k = l;
    while (i < n1 && j < n2) {
        if (L[i] <= R[j]) {
            arr[k] = L[i];
            i++;
        }
        else {
            arr[k] = R[j];
            j++;
        }
        k++;
    }

    // Copy the remaining elements of L[],
    // if there are any
    while (i < n1) {
        arr[k] = L[i];
        i++;
        k++;
    }

    // Copy the remaining elements of R[],
    // if there are any
    while (j < n2) {
        arr[k] = R[j];
        j++;
        k++;
    }
}

// l is for left index and r is right index of the
// sub-array of arr to be sorted
void mergeSort(int arr[], int l, int r)
{
    if (l < r) {
        int m = l + (r - l) / 2;

        // Sort first and second halves
        mergeSort(arr, l, m);
        mergeSort(arr, m + 1, r);

        merge(arr, l, m, r);
    }
}

// Function to print an array
void printArray(int A[], int size)
{
    int i;
    for (i = 0; i < size; i++)
        printf("%d ", A[i]);
    printf("\n");
}

// Driver code
int main()
{
    int arr[] = { 12, 11, 13, 5, 6, 7 };
    int arr_size = sizeof(arr) / sizeof(arr[0]);

    printf("Given array is \n");
    printArray(arr, arr_size);

    mergeSort(arr, 0, arr_size - 1);

    printf("\nSorted array is \n");
    printArray(arr, arr_size);
    return 0;
}

// Java program for Merge Sort
import java.io.*;

class MergeSort {

    // Merges two subarrays of arr[].
    // First subarray is arr[l..m]
    // Second subarray is arr[m+1..r]
    void merge(int arr[], int l, int m, int r)
    {
        // Find sizes of two subarrays to be merged
        int n1 = m - l + 1;
        int n2 = r - m;

        // Create temp arrays
        int L[] = new int[n1];
        int R[] = new int[n2];

        // Copy data to temp arrays
        for (int i = 0; i < n1; ++i)
            L[i] = arr[l + i];
        for (int j = 0; j < n2; ++j)
            R[j] = arr[m + 1 + j];

        // Merge the temp arrays

        // Initial indices of first and second subarrays
        int i = 0, j = 0;

        // Initial index of merged subarray array
        int k = l;
        while (i < n1 && j < n2) {
            if (L[i] <= R[j]) {
                arr[k] = L[i];
                i++;
            }
            else {
                arr[k] = R[j];
                j++;
            }
            k++;
        }

        // Copy remaining elements of L[] if any
        while (i < n1) {
            arr[k] = L[i];
            i++;
            k++;
        }

        // Copy remaining elements of R[] if any
        while (j < n2) {
            arr[k] = R[j];
            j++;
            k++;
        }
    }

    // Main function that sorts arr[l..r] using
    // merge()
    void sort(int arr[], int l, int r)
    {
        if (l < r) {

            // Find the middle point
            int m = l + (r - l) / 2;

            // Sort first and second halves
            sort(arr, l, m);
            sort(arr, m + 1, r);

            // Merge the sorted halves
            merge(arr, l, m, r);
        }
    }

    // A utility function to print array of size n
    static void printArray(int arr[])
    {
        int n = arr.length;
        for (int i = 0; i < n; ++i)
            System.out.print(arr[i] + " ");
        System.out.println();
    }

    // Driver code
    public static void main(String args[])
    {
        int arr[] = { 12, 11, 13, 5, 6, 7 };

        System.out.println("Given array is");
        printArray(arr);

        MergeSort ob = new MergeSort();
        ob.sort(arr, 0, arr.length - 1);

        System.out.println("\nSorted array is");
        printArray(arr);
    }
}
/* This code is contributed by Rajat Mishra */

# Merges two subarrays of array[].
# First subarray is arr[left..mid]
# Second subarray is arr[mid+1..right]
def merge(array, left, mid, right):
    subArrayOne = mid - left + 1
    subArrayTwo = right - mid

    # Create temp arrays
    leftArray = [0] * subArrayOne
    rightArray = [0] * subArrayTwo

    # Copy data to temp arrays leftArray[] and rightArray[]
    for i in range(subArrayOne):
        leftArray[i] = array[left + i]
    for j in range(subArrayTwo):
        rightArray[j] = array[mid + 1 + j]

    indexOfSubArrayOne = 0  # Initial index of first sub-array
    indexOfSubArrayTwo = 0  # Initial index of second sub-array
    indexOfMergedArray = left  # Initial index of merged array

    # Merge the temp arrays back into array[left..right]
    while indexOfSubArrayOne < subArrayOne and indexOfSubArrayTwo < subArrayTwo:
        if leftArray[indexOfSubArrayOne] <= rightArray[indexOfSubArrayTwo]:
            array[indexOfMergedArray] = leftArray[indexOfSubArrayOne]
            indexOfSubArrayOne += 1
        else:
            array[indexOfMergedArray] = rightArray[indexOfSubArrayTwo]
            indexOfSubArrayTwo += 1
        indexOfMergedArray += 1

    # Copy the remaining elements of left[], if any
    while indexOfSubArrayOne < subArrayOne:
        array[indexOfMergedArray] = leftArray[indexOfSubArrayOne]
        indexOfSubArrayOne += 1
        indexOfMergedArray += 1

    # Copy the remaining elements of right[], if any
    while indexOfSubArrayTwo < subArrayTwo:
        array[indexOfMergedArray] = rightArray[indexOfSubArrayTwo]
        indexOfSubArrayTwo += 1
        indexOfMergedArray += 1

# begin is for left index and end is right index
# of the sub-array of arr to be sorted
def mergeSort(array, begin, end):
    if begin >= end:
        return

    mid = begin + (end - begin) // 2
    mergeSort(array, begin, mid)
    mergeSort(array, mid + 1, end)
    merge(array, begin, mid, end)

# Function to print an array
def printArray(array, size):
    for i in range(size):
        print(array[i], end=" ")
    print()

# Driver code
if __name__ == "__main__":
    arr = [12, 11, 13, 5, 6, 7]
    arr_size = len(arr)

    print("Given array is")
    printArray(arr, arr_size)

    mergeSort(arr, 0, arr_size - 1)

    print("\nSorted array is")
    printArray(arr, arr_size)

// C# program for Merge Sort
using System;

class MergeSort {

    // Merges two subarrays of []arr.
    // First subarray is arr[l..m]
    // Second subarray is arr[m+1..r]
    void merge(int[] arr, int l, int m, int r)
    {
        // Find sizes of two
        // subarrays to be merged
        int n1 = m - l + 1;
        int n2 = r - m;

        // Create temp arrays
        int[] L = new int[n1];
        int[] R = new int[n2];
        int i, j;

        // Copy data to temp arrays
        for (i = 0; i < n1; ++i)
            L[i] = arr[l + i];
        for (j = 0; j < n2; ++j)
            R[j] = arr[m + 1 + j];

        // Merge the temp arrays

        // Initial indexes of first
        // and second subarrays
        i = 0;
        j = 0;

        // Initial index of merged
        // subarray array
        int k = l;
        while (i < n1 && j < n2) {
            if (L[i] <= R[j]) {
                arr[k] = L[i];
                i++;
            }
            else {
                arr[k] = R[j];
                j++;
            }
            k++;
        }

        // Copy remaining elements
        // of L[] if any
        while (i < n1) {
            arr[k] = L[i];
            i++;
            k++;
        }

        // Copy remaining elements
        // of R[] if any
        while (j < n2) {
            arr[k] = R[j];
            j++;
            k++;
        }
    }

    // Main function that
    // sorts arr[l..r] using
    // merge()
    void sort(int[] arr, int l, int r)
    {
        if (l < r) {

            // Find the middle point
            int m = l + (r - l) / 2;

            // Sort first and second halves
            sort(arr, l, m);
            sort(arr, m + 1, r);

            // Merge the sorted halves
            merge(arr, l, m, r);
        }
    }

    // A utility function to
    // print array of size n
    static void printArray(int[] arr)
    {
        int n = arr.Length;
        for (int i = 0; i < n; ++i)
            Console.Write(arr[i] + " ");
        Console.WriteLine();
    }

    // Driver code
    public static void Main(String[] args)
    {
        int[] arr = { 12, 11, 13, 5, 6, 7 };
        Console.WriteLine("Given array is");
        printArray(arr);
        MergeSort ob = new MergeSort();
        ob.sort(arr, 0, arr.Length - 1);
        Console.WriteLine("\nSorted array is");
        printArray(arr);
    }
}

// This code is contributed by Princi Singh

// JavaScript program for Merge Sort

// Merges two subarrays of arr[].
// First subarray is arr[l..m]
// Second subarray is arr[m+1..r]
function merge(arr, l, m, r)
{
    var n1 = m - l + 1;
    var n2 = r - m;

    // Create temp arrays
    var L = new Array(n1); 
    var R = new Array(n2);

    // Copy data to temp arrays L[] and R[]
    for (var i = 0; i < n1; i++)
        L[i] = arr[l + i];
    for (var j = 0; j < n2; j++)
        R[j] = arr[m + 1 + j];

    // Merge the temp arrays back into arr[l..r]

    // Initial index of first subarray
    var i = 0;

    // Initial index of second subarray
    var j = 0;

    // Initial index of merged subarray
    var k = l;

    while (i < n1 && j < n2) {
        if (L[i] <= R[j]) {
            arr[k] = L[i];
            i++;
        }
        else {
            arr[k] = R[j];
            j++;
        }
        k++;
    }

    // Copy the remaining elements of
    // L[], if there are any
    while (i < n1) {
        arr[k] = L[i];
        i++;
        k++;
    }

    // Copy the remaining elements of
    // R[], if there are any
    while (j < n2) {
        arr[k] = R[j];
        j++;
        k++;
    }
}

// l is for left index and r is
// right index of the sub-array
// of arr to be sorted
function mergeSort(arr,l, r){
    if(l>=r){
        return;
    }
    var m =l+ parseInt((r-l)/2);
    mergeSort(arr,l,m);
    mergeSort(arr,m+1,r);
    merge(arr,l,m,r);
}

// Function to print an array
function printArray( A, size)
{
    for (var i = 0; i < size; i++)
       console.log(  A[i] + " ");
}


var arr = [ 12, 11, 13, 5, 6, 7 ];
    var arr_size = arr.length;

    console.log(  "Given array is ");
    printArray(arr, arr_size);

    mergeSort(arr, 0, arr_size - 1);

    console.log( "Sorted array is ");
    printArray(arr, arr_size);

// This code is contributed by SoumikMondal

<?php
/* PHP recursive program for Merge Sort */

// Merges two subarrays of arr[].
// First subarray is arr[l..m]
// Second subarray is arr[m+1..r]
function merge(&$arr, $l, $m, $r)
{
    $n1 = $m - $l + 1;
    $n2 = $r - $m;

    // Create temp arrays
    $L = array();
    $R = array();
  
    // Copy data to temp arrays L[] and R[]
    for ($i = 0; $i < $n1; $i++)
        $L[$i] = $arr[$l + $i];
    for ($j = 0; $j < $n2; $j++)
        $R[$j] = $arr[$m + 1 + $j];

    // Merge the temp arrays back into arr[l..r]
    $i = 0;
    $j = 0;
    $k = $l;
    while ($i < $n1 && $j < $n2) {
        if ($L[$i] <= $R[$j]) {
            $arr[$k] = $L[$i];
            $i++;
        }
        else {
            $arr[$k] = $R[$j];
            $j++;
        }
        $k++;
    }

    // Copy the remaining elements of L[], 
    // if there are any
    while ($i < $n1) {
        $arr[$k] = $L[$i];
        $i++;
        $k++;
    }

    // Copy the remaining elements of R[], 
    // if there are any
    while ($j < $n2) {
        $arr[$k] = $R[$j];
        $j++;
        $k++;
    }
}

// l is for left index and r is right index of the
// sub-array of arr to be sorted
function mergeSort(&$arr, $l, $r)
{
    if ($l < $r) {
        $m = $l + (int)(($r - $l) / 2);

        // Sort first and second halves
        mergeSort($arr, $l, $m);
        mergeSort($arr, $m + 1, $r);

        merge($arr, $l, $m, $r);
    }
}

// Function to print an array
function printArray($A, $size)
{
    for ($i = 0; $i < $size; $i++)
        echo $A[$i]." ";
    echo "\n";
}

// Driver code
$arr = array(12, 11, 13, 5, 6, 7);
$arr_size = sizeof($arr);

echo "Given array is \n";
printArray($arr, $arr_size);

mergeSort($arr, 0, $arr_size - 1);

echo "\nSorted array is \n";
printArray($arr, $arr_size);
return 0;

//This code is contributed by Susobhan Akhuli
?>

Given array is 
12 11 13 5 6 7 

Sorted array is 
5 6 7 11 12 13 

Complexity Analysis of Merge Sort:

Time Complexity:

• Best Case: O(n log n), When the array is already sorted or nearly sorted.
• Average Case: O(n log n), When the array is randomly ordered.
• Worst Case: O(n log n), When the array is sorted in reverse order.

Space Complexity: O(n), Additional space is required for the temporary array used during merging.

Advantages of Merge Sort:

• Stability: Merge sort is a stable sorting algorithm, which means it maintains the relative order of equal elements in the input array.
• Guaranteed worst-case performance: Merge sort has a worst-case time complexity of O(N logN), which means it performs well even on large datasets.
• Simple to implement: The divide-and-conquer approach is straightforward.

Disadvantage of Merge Sort:

• Space complexity: Merge sort requires additional memory to store the merged sub-arrays during the sorting process. 
• Not in-place: Merge sort is not an in-place sorting algorithm, which means it requires additional memory to store the sorted data. This can be a disadvantage in applications where memory usage is a concern.

Applications of Merge Sort:

• Sorting large datasets
• External sorting (when the dataset is too large to fit in memory)
• Inversion counting (counting the number of inversions in an array)
• Finding the median of an array

Quick Links:

• Recent Articles on Merge Sort
• Top Sorting Interview Questions and Problems
• Practice problems on Sorting algorithm
• Quiz on Merge Sort

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