Ternary Search

Like the binary search, it also separates the lists into sub-lists. This procedure divides the list into three parts using two intermediate mid values. As the lists are divided into more subdivisions, so it reduces the time to search a key value.

The complexity of Ternary Search Technique

• Time Complexity: O(log3 n)
• Space Complexity: O(1)

Input and Output

Input:
A sorted list of data: 12 25 48 52 67 79 88 93
The search key 52
Output:
Item found at location: 3

Algorithm

ternarySearch(array, start, end, key)

Input − An sorted array, start and end location, and the search key

Output − location of the key (if found), otherwise wrong location.

Begin
   if start  array[midSecond] then
         call ternarySearch(array, midFirst+1, end, key)
      else
         call ternarySearch(array, midFirst+1, midSecond-1, key)
   else
      return invalid location
End

Example

#include
using namespace std;

int ternarySearch(int array[], int start, int end, int key) {
   if(start  array[midSecond])
         return ternarySearch(array, midSecond+1, end, key);
      return ternarySearch(array, midFirst+1, midSecond-1, key);
   }
   return -1;
}

int main() {
   int n, searchKey, loc;
   cout > n;
   int arr[n]; //create an array of size n
   cout > arr[i];
   }

   cout > searchKey;
   if((loc = ternarySearch(arr, 0, n, searchKey)) >= 0)
      cout 
Output
Enter number of items: 8
Enter items:
12 25 48 52 67 79 88 93
Enter search key to search in the list: 52
Item found at location: 3