It divides the input array into two halves, calls itself for the two halves, and then merges the two sorted halves. The merge() function is used for merging two halves. The merge(arr, l, m, r) is a key process that assumes that arr[l…m] and arr[m+1…r] are sorted and merges the two sorted sub-arrays into one. See the following C implementation for details.
MergeSort(arr[], l, r)
If r > l
- Find the middle point to divide the array into two halves:
middle m = l+ (r-l)/2 - Call mergeSort for first half:
Call mergeSort(arr, l, m) - Call mergeSort for second half:
Call mergeSort(arr, m+1, r) - Merge the two halves sorted in step 2 and 3:
Call merge(arr, l, m, r)
/* Java program for Merge Sort */
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 indexes of first and second subarrays
int i = 0, j = 0;
// Initial index of merged subarry 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");
printArray(arr);
MergeSort ob = new MergeSort();
ob.sort(arr, 0, arr.length - 1);
System.out.println("\nSorted array");
printArray(arr);
}
}
Output
Given array is
12 11 13 5 6 7
Sorted array is
5 6 7 11 12 13
Time Complexity: Sorting arrays on different machines. Merge Sort is a recursive algorithm and time complexity can be expressed as following recurrence relation.
T(n) = 2T(n/2) + θ(n)
The above recurrence can be solved either using the Recurrence Tree method or the Master method. It falls in case II of Master Method and the solution of the recurrence is θ(nLogn). Time complexity of Merge Sort is θ(nLogn) in all 3 cases (worst, average and best) as merge sort always divides the array into two halves and takes linear time to merge two halves.
Auxiliary Space: O(n)
Algorithmic Paradigm: Divide and Conquer
Sorting In Place: No in a typical implementation
Stable: Yes