Commonly Asked Interview Questions on Searching Algorithm

Question 1: What is a searching algorithm?

Answer: A searching algorithm is a method used to find a specific item within a collection of data. Searching Algorithms are designed to check for an element or retrieve an element from any data structure where it is stored.

Question 2: What are the different types of searching algorithms?

Answer: Searching algorithms include Linear Search, Binary Search, Depth-First Search (DFS), Breadth-First Search (BFS), and Hashing, each with its own approach to find elements.

Question 3: Explain Linear Search and its time complexity.

Answer: Linear Search checks each element in a list one by one until finding the target or reaching the end. Its time complexity is O(n) in the worst case.

Question 4: How does Binary Search work?

Answer: Binary Search divides a sorted array in half repeatedly, narrowing down the search space by comparing the target with the mid until finding the target or exhausting the elements. Its time complexity is O(log n).

Question 5: What are the requirements for using Binary Search?

Answer: Binary Search requires a sorted array and the ability to access elements by index for efficient traversal.

Question: 6 Explain why complexity of Binary search is O (log₂n) ?

Answer: Binary search halves the search space with each step, reducing the number of elements to be searched by half each time. This logarithmic reduction results in a time complexity of O(log₂n), where n is the number of elements in the sorted array.

Question 7: How does Hashing work in searching?

Answer: Hashing uses a hash function to compute an index for each element, allowing for constant-time search operations in the average case by storing elements in a hash table.

Question 8: Compare Linear Search and Binary Search.

Answer: Linear Search checks elements sequentially, while Binary Search halves the search space with each step, making it more efficient for sorted data with a time complexity of O(log n).

Question 9: Recursive and Iterative Binary Search: Which one is more efficient and why?

Answer: Iterative Binary Search is typically more efficient than Recursive Binary Search. This is because iterative binary search avoids the overhead of recursive function calls and stack space consumption, resulting in lower memory usage and potentially faster execution, especially for large datasets.

Question 10: Why use binary search if there is a ternary search?

Answer: Binary search is preferred for finding specific values in sorted arrays, as it divides the search space in half with each step, resulting in efficient searches with a time complexity of O(log₂n). Binary Search is useful for finding maximum or minimum value in a Monotonic function whereas Ternary search is useful for finding the maximum or minimum value in a unimodal function. Also, the time complexity of Ternary Search is O(2 * log₃N) which is greater than O(log₂N).

Question 11: When is each searching algorithm most appropriate to use?

Answer: Choose the appropriate searching algorithm based on factors like data structure, data size, and desired search efficiency, such as Binary Search for sorted arrays and Hashing for constant-time searches.

For tech job interviews, knowing about algorithms is really important. Being good at algorithms shows you can solve problems effectively and make programs run faster. This article has lots of common interview questions about algorithms.