Binary Search Algorithm Questions

Mahesh pal

Score: 🔥 44

Beginner

Took 2 months

DSA

Binary Search Algorithm

86%

Questions Attempted

14 / 15

Correct Answers

Incorrect Answers

Points Earned

🔥 13

Question 1

What is the primary advantage of using binary search over linear search for a sorted array?

Binary search uses less memory.
Binary search is easier to implement.
Binary search has a faster time complexity in most cases.
Binary search can handle duplicate elements more efficiently.

Explanation:

Binary search's logarithmic time complexity makes it significantly faster than linear search's linear time complexity for larger datasets.

Question 2

When searching for a value in a very large sorted array, which algorithm is generally more efficient?

Linear search
Binary search

Explanation:

As the size of the sorted array grows, the efficiency of binary search becomes increasingly apparent. Its logarithmic time complexity makes it significantly faster than linear search for large datasets.

Question 3

In the context of Binary Search, what is the problem with searching in an infinitely sized array?

Binary Search cannot handle arrays with no defined end.
Binary Search requires the entire array to be loaded into memory.
Binary Search is too slow for infinitely sized arrays.
Binary Search cannot handle duplicate elements in an infinitely sized array.

Explanation:

Standard Binary Search requires a defined search space with a start and an end. Infinite arrays lack this defined end, making the classic algorithm inapplicable.

Question 4

In binary search, what happens if the target value is less than the middle element of the current search interval?

The search continues in the left half of the interval.
The search continues in the right half of the interval.
The search terminates as the target is not found.
The middle element is compared with its adjacent elements.

Explanation:

Since the array is sorted, if the target is less than the middle, it must reside in the left portion.

Question 5

Which of the following is a prerequisite for using binary search on a dataset?

The data must be sorted.
The data must be stored in a linked list.
The data must contain only numerical values.
The data must be stored in a hash table.

Explanation:

Binary search relies on the data being sorted to repeatedly narrow down the search interval. Without a sorted dataset, you cannot effectively determine which half to discard in each step.

Question 6

What is the time complexity of Binary Search in the best-case scenario?

O(n)
O(log n)
O(1)
O(n log n)

Explanation:

In the best case, the target element is found in the middle of the array on the first comparison, resulting in constant time.

Question 7

You need to find the first occurrence of a target value in a sorted array with duplicates. Which algorithm is more efficient?

Linear search
Binary search

Explanation:

Even with duplicates, a modified binary search can efficiently locate the first occurrence of a target value by continuing to search in the left half after a match is found until it reaches the first instance.

Question 8

Which data structure inherently benefits from the efficiency of binary search for searching operations?

Linked List
Queue
Binary Search Tree
Hash Table

Explanation:

Binary Search Trees are specifically structured to leverage the efficiency of binary search. Their properties ensure a logarithmic time complexity for search, insertion, and deletion operations.

Question 9

You have an unsorted array, and you need to find a specific value. Is it more efficient to sort the array and then use binary search, or to directly apply linear search?

Sort and then use binary search
Directly use linear search

Explanation:

Sorting an array itself generally has a time complexity of O(n log n). If you only need to find one value, linear search's O(n) complexity is more efficient than sorting followed by binary search.

Question 10

In the worst-case scenario, how many comparisons will binary search perform on a sorted array of 16 elements?

Explanation:

With each comparison, the search space is halved. 16 -> 8 -> 4 -> 2 -> 1. This takes 4 comparisons.

Question 11

What is the key characteristic of an array that makes Binary Search applicable?

The array must be sorted.
The array must be of a fixed size.
The array must contain only positive integers.
The array must be stored in contiguous memory locations.

Explanation:

Binary Search fundamentally relies on the array being sorted. It repeatedly divides the search interval in half, which is only efficient and correct if the array is sorted.

Question 12

What is the time complexity of Binary Search in the worst-case scenario?

O(n)
O(log n)
O(1)
O(n log n)

Explanation:

Binary Search halves the search space in each step, leading to a logarithmic time complexity. In the worst case, we perform log n comparisons.

Question 13

In Binary Search, if the target value is less than the middle element, what should be the next step?

Search the right half of the array.
Search the left half of the array.
Search the entire array again.
Conclude the target is not present.

Explanation:

If the target is less than the middle, it can only be present in the left portion of the sorted array.

Question 14

What is the space complexity of Binary Search (iterative implementation)?

O(1)
O(n)
O(log n)
O(n log n)

Explanation:

Iterative Binary Search uses a constant amount of extra space for variables, regardless of the input array size.