COURTESY:GEEKSFORGEEKS
Binary
Search
Given a sorted array arr[] of n elements, write a function to
search a given element x in arr[].
A simple approach is to do linear search, i.e.,
start from the leftmost element of arr[] and one by one compare x with each
element of arr[], if x matches with an element, return the index. If x doesn’t
match with any of elements, return -1.
// Linearly search x in arr[]. If x is
present then return its
// location, otherwise return -1
int search(int arr[], int n, int x)
{
int i;
for (i=0; i<n; i++)
if (arr[i] == x)
return i;
return -1;
}
|
The time complexity of
above algorithm is O(n).
The idea of binary search is to use the information that the array
is sorted and reduce the time complexity to O(Logn). We basically ignore half
of the elements just after one comparison.
1) Compare x with the middle element.
2) If x matches with middle element, we return the mid index.
3) Else If x is greater than the mid element, then x can only lie in right half subarray after the mid element. So we recur for right half.
4) Else (x is smaller) recur for the left half.
1) Compare x with the middle element.
2) If x matches with middle element, we return the mid index.
3) Else If x is greater than the mid element, then x can only lie in right half subarray after the mid element. So we recur for right half.
4) Else (x is smaller) recur for the left half.
Following is Recursive C
implementation of Binary Search.
#include <stdio.h>
// A recursive binary search function. It
returns location of x in
// given array arr[l..r] is present,
otherwise -1
int binarySearch(int arr[], int l, int r, int x)
{
if (r >= l)
{
int mid = l + (r - l)/2;
//
If the element is present at the middle itself
if (arr[mid] == x) return mid;
//
If element is smaller than mid, then it can only be present
//
in left subarray
if (arr[mid] > x) return binarySearch(arr, l,
mid-1, x);
//
Else the element can only be present in right subarray
return binarySearch(arr, mid+1, r, x);
}
// We reach here when
element is not present in array
return -1;
}
int main(void)
{
int arr[] = {2, 3, 4, 10, 40};
int n = sizeof(arr)/ sizeof(arr[0]);
int x = 10;
int result = binarySearch(arr, 0, n-1, x);
(result == -1)?
printf("Element is not present in array")
:
printf("Element is present at index %d", result);
return 0;
}
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Output:
Element is present at index 3
Following is Iterative C
implementation of Binary Search.
#include <stdio.h>
// A iterative binary search function. It
returns location of x in
// given array arr[l..r] if present,
otherwise -1
int binarySearch(int arr[], int l, int r, int x)
{
while (l <= r)
{
int m = l + (r-l)/2;
if (arr[m] == x) return m; // Check if
x is present at mid
if (arr[m] < x) l = m + 1; // If x greater, ignore left half
else r = m - 1; // If x is smaller, ignore right half
}
return -1; // if we reach here, then element was not present
}
int main(void)
{
int arr[] = {2, 3, 4, 10, 40};
int n = sizeof(arr)/ sizeof(arr[0]);
int x = 10;
int result = binarySearch(arr, 0, n-1, x);
(result == -1)?
printf("Element is not present in array")
:
printf("Element is present at index %d", result);
return 0;
}
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Output:
Element is present at index 3
Time Complexity:
The time complexity of Binary Search can be written as
The time complexity of Binary Search can be written as
T(n) = T(n/2) + c
The above recurrence can
be solved either using Recurrence T ree method or Master method. It falls in
case II of Master Method and solution of the recurrence is
.
Auxiliary Space: O(1) in case of iterative implementation. In case of
recursive implementation, O(Logn) recursion call stack space.
Algorithmic Paradigm: Divide and Conquer
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