Table of Contents
- 1 What is the maximum number of comparisons in binary search?
- 2 What is the maximum number of comparisons that a binary search method will make when searching for a value in a 1000 element array?
- 3 What is the largest number of comparisons a linear search might have to make when searching an array of length n?
- 4 What is the Big O for binary search?
- 5 What is the minimum and maximum number nodes possible on a level 5 binary search tree?
- 6 What is the worst case of a binary search?
- 7 How many elements are there in a binary search?
What is the maximum number of comparisons in binary search?
8. Efficiency Comparison
| Size of List | Maximum Number of Comparisons | |
|---|---|---|
| Linear Search | Binary Search | |
| 100,000 | 100,000 | 16 |
| 200,000 | 200,000 | 17 |
| 400,000 | 400,000 | 18 |
What is the maximum number of comparisons that a binary search method will make when searching for a value in a 1000 element array?
10 guesses
Therefore, for a 1000-element array, binary search would require at most 10 guesses.
What is the maximum number of iterations a binary search will make to find some number in the array?
If we have an array of 1024 elements, the maximum number of iterations (or method calls in the case of a recursive implementation) is log2(1024) = 10 because 210 = 1024.
What is the maximum number of comparisons needed by the binary search algorithm when an array contains 1024 elements?
11 comparisons
Answer and Explanation: For a sorted list of 1024 elements, a binary search takes at most 11 comparisons.
What is the largest number of comparisons a linear search might have to make when searching an array of length n?
The maximum number of comparisons performed by the linear search on an array of N elements is N/2 (assuming the search values are consistently found).
What is the Big O for binary search?
In general, the worst-case scenario of a Binary Search is Log of n + 1. The Big O notation for Binary Search is O(log N). In contrast to O(N) which takes an additional step for each data element, O(log N) means that the algorithm takes an additional step each time the data doubles.
What is the big O runtime of the binary search algorithm in the best average and worst cases?
The time complexity of the binary search algorithm is O(log n). The best-case time complexity would be O(1) when the central index would directly match the desired value. The worst-case scenario could be the values at either extremity of the list or values not in the list.
How do you calculate the Big O value?
To calculate Big O, there are five steps you should follow:
- Break your algorithm/function into individual operations.
- Calculate the Big O of each operation.
- Add up the Big O of each operation together.
- Remove the constants.
- Find the highest order term — this will be what we consider the Big O of our algorithm/function.
What is the minimum and maximum number nodes possible on a level 5 binary search tree?
All the rules in BST are same as in binary tree and can be visualized in the same way. Solution: According to formula discussed, max number of nodes = 2^(h+1)-1 = 2^6-1 =63. min number of nodes = h+1 = 5+1 = 6.
What is the worst case of a binary search?
The worst case of a binary search is when you search for the first element or the last element in the array or search for an element which does not exist in the array and is lower than the first element in the array or higher than the last element in the array.
Can binary search be done in constant time?
This comparison can be done in constant time. Binary search is a divide-and-conquer algorithm. To find an element in a sorted array, A, we first compare the search element with A [ n 2], and recurse either on the first half, A [ 0, …, n 2 – 1], or on the second half, A [ n 2, …, n − 1].
How do you find the maximum of a binary search tree?
In Binary Search Tree, we can find maximum by traversing right pointers until we reach the rightmost node. But in Binary Tree, we must visit every node to figure out maximum.
How many elements are there in a binary search?
Write the code and see. But if you want to think about the answer, look at how a binary search works. You’ll have an array a with 1000 elements (elements 0 – 999). You’re looking for value. Let’s say the element is always to the left of where we look, because the numbers are easy.