Quick Answer: Why Is It Always Good To Find The Middle Value Using Bit Manipulation Mid=(end-start)>>1+start?


In which search we need to find mid value?

If the middle -most element is equal to key, we ‘ve found the key. If the middle -most element is greater than the key, we search on the left half of the middle -most element, else we search on the right half. int mid = (low + high) / 2; But calculating mid this way is ineffective.

How do you find the middle element of a binary search?

Binary Search

  1. mid = (start + end)/2.
  2. mid = start + (end-start)/2;
  3. Say we are given a 2D integer array and we need to sort the array in ascending order based on the second value of each row(or second element of each 1D array).
  4. Arrays.
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How do you find the middle element of an array by value?

8 Answers. int mid = firstIndex + (lastIndex-firstIndex)/2, will give you the mid of the array.

How do you find the middle of an array?

int mid = nums[nums. Length/2]; You take the size of the array ( nums. Length ), divide by two to get the index in the middle and use that index.

Is binary search faster than linear?

Binary search is faster than linear search except for small arrays. However, the array must be sorted first to be able to apply binary search. There are specialized data structures designed for fast searching, such as hash tables, that can be searched more efficiently than binary search.

What are the limitations of binary search?

The major limitation of binary search is that there is a need for the sorted array to perform the binary search operation. If the array is not sorted the output is either not correct or maybe after a long number of steps and according to the data structure, the output should come in a minimum number of steps.

What are the steps of binary search?

Binary Search Algorithm

  1. Step 1 – Read the search element from the user.
  2. Step 2 – Find the middle element in the sorted list.
  3. Step 3 – Compare the search element with the middle element in the sorted list.
  4. Step 4 – If both are matched, then display “Given element is found!!!” and terminate the function.

What is overflow in binary search?

could cause an overflow error if left + right is more than what int can store. The user of search would not expect such flow when the array is large enough. This bug was even in the java library for few years before it was discovered and fixed, which tells you how easy it is to implement this search incorrectly.

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What is the stopping condition in binary search?

The binary search algorithm can be stated clearly using recursion. The stopping cases are: The array would have no elements ( Slice’First>Slice’Last or Slice’Length=0 ). The middle value is the target value.

How do you find the middle element of a linked list?

Traverse linked list using two pointers. Move one pointer by one and the other pointers by two. When the fast pointer reaches the end slow pointer will reach the middle of the linked list.

How can you find middle element of an array without using length?

Find the middle of the string or array with an unknown length. You may not traverse the list to find the length. You may not use anything to help you find the length – as it is “unknown.” (ie. no sizeof (C) or count(C#) etc)

How do you find the middle digit of a number?

The middle digit of a number is that which is exactly in-mid of the given number N is called middle digit number. If a number has two middle digits then print both the digits as the middle number.

How do you find the middle of a list in Python?

To get the length of a list, we are using len( list ) method. len( list ) method returns the length of a list. Dividing this value by 2 will give us the middle position.

How do you find the middle element of a matrix?

Approach: The middle element of the matrix of odd order will be located at the position mat[n / 2][n / 2].

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How do you find the most repeated number in an array?


  1. Start.
  2. Declare the array.
  3. Initialize the array.
  4. Call the function that will return the most occurring element.
  5. Declare two for loops.
  6. The first for loop will hold each element.
  7. The second for loop will check for duplicate elements.
  8. If duplicate elements found, increment the count.

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