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.

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

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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....

Implementation of Merge Sort:

C++ // C++ program for Merge Sort #include 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 // C program for Merge Sort #include #include // 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 // 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 */ Python # 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# // 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 // 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 ...

Complexity Analysis of Merge Sort:

Time Complexity:...

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 datasetsExternal 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...

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