DATA STRUCTURES

Merge Sort Algorithm

Merge Sort follows the rule of Divide and Conquer. In merge sort the unsorted list is divided into N sublists, each having one element, because a list consisting of one element is always sorted. Then, it repeatedly merges these sublists, to produce new sorted sublists, and in the end, only one sorted list is produced.

Merge Sort is quite fast, and has a time complexity of O(n log n). It is also a stable sort, which means the "equal" elements are ordered in the same order in the sorted list.


How Merge Sort Works

Merge Sorting in Data Structures


Like we can see in the above example, merge sort first breaks the unsorted list into sorted sublists, each having one element, because a list of one element is considered sorted and then it keeps merging these sublists, to finally get the complete sorted list.


Sorting using Merge Sort Algorithm

/*  a[] is the array, p is starting index, that is 0, 
and r is the last index of array.  */

//Lets take a[5] = {32, 45, 67, 2, 7} as the array to be sorted.

void mergesort(int a[], int p, int r)
{
  int q;
  if(p < r)
  {
    q = floor( (p+r) / 2);
    mergesort(a, p, q);
    mergesort(a, q+1, r);
    merge(a, p, q, r);
  }
}

void merge(int a[], int p, int q, int r)
{
  int b[5];     //same size of a[]
  int i, j, k;
  k = 0;
  i = p;
  j = q+1;
  while(i <= q && j <= r)
  {
    if(a[i] < a[j])
    {
      b[k++] = a[i++];       // same as b[k]=a[i]; k++; i++;
    }
    else
    {
      b[k++] = a[j++];
    }
  }
  
  while(i <= q)
  {
    b[k++] = a[i++];
  }
  
  while(j <= r)
  {
    b[k++] = a[j++];
  }
  
  for(i=r; i >= p; i--)
  {
    a[i] = b[--k];        // copying back the sorted list to a[]
  } 

}

Complexity Analysis of Merge Sort

Worst Case Time Complexity : O(n log n)
Best Case Time Complexity : O(n log n)
Average Time Complexity : O(n log n)
Space Complexity : O(n)
  • Time complexity of Merge Sort is O(n Log n) in all 3 cases (worst, average and best) as merge sort always divides the array in two halves and take linear time to merge two halves.
  • It requires equal amount of additional space as the unsorted list. Hence its not at all recommended for searching large unsorted lists.
  • It is the best Sorting technique used for sorting Linked Lists.