This set of Data Structures & Algorithms Multiple Choice Questions & Answers (MCQs) focuses on “Hash Tables Chaining with Binary Trees”.

**1. What is the time complexity of the delete function in the hash table using a binary tree?A) O(1)**

B) O(n)

C) O(log n)

D) O(n log n)

Explanation: The delete function in a hash table has an O time complexity (1). The hash function must be designed in such a way that the number of collisions is minimal.

**2. What is the advantage of a hash table over BST?A) hash table has a better average time complexity for performing insert, delete and search operations**

B) hash table requires less space

C) range query is easy with hash table

D) easier to implement

Explanation: Both a hash table and a binary search tree (BST) are examples of data structures. The benefit of a hash table is that it has a lower time complexity for insert, delete, and search operations.

**3. What is the disadvantage of BST over the hash table?**

A) BST is easier to implement

B) BST can get the keys sorted by just performing inorder traversal

C) BST can perform range query easily**D) Time complexity of hash table in inserting, searching and deleting is less than that of BST**

Explanation: BST has the benefits of being easier to implement, having the ability to sort keys using only in-order traversal, and having the ability to perform range queries. Insert, erase, and search operations on a hash table are less time consuming.

**4. Which of the following technique stores data separately in case of a collision?**

A) Open addressing

B) Double hashing

C) Quadratic probing**D) Chaining using a binary tree**

Explanation: In the event of a collision, open addressing is used to store data in the table itself. Chaining, on the other hand, stores data in a different body.

**5. Separate chaining is easier to implement as compared to open addressing.A) true**

B) false

Explanation: In a hash table, there are two ways to handle collisions: open addressing and separate chaining. When compared to separate chaining, open addressing necessitates further computation.

**6. In open addressing the hash table can never become full.**

A) True**B) False**

Explanation: In a hash table, there are two ways to handle collisions: open addressing and separate chaining. The hash table may become complete in open addressing.

**7. Which of the following variant of a hash table has the best cache performance?**

A) hash table using a linked list for separate chaining

B) hash table using binary search tree for separate chaining**C) hash table using open addressing**

D) hash table using a doubly linked list for separate chaining

Explanation: As compared to separate chaining, the hash table implementation using open addressing has a better cache efficiency. It’s because open addressing keeps all of the data in the same table, saving space.

**8. What is the advantage of hashing with chaining?**

A) cache performance is good

B) uses less space**C) less sensitive to hash function**

D) has a time complexity of O(n) in the worst case

Explanation: Separate chaining hashing has the benefit of being less responsive to a hash feature. It’s also easy to put into practise.

**9. What is the disadvantage of hashing with chaining?**

A) not easy to implement**B) takes more space**

C) quite sensitive to hash function

D) table gets filled up easily

Explanation: Separate chaining has the downside of taking up more room while hashing. In the event of a collision, this space is used to store elements.

**10. What is the time complexity of insert function in a hash table using a binary tree?A) O(1)**

B) O(n)

C) O(log n)

D) O(n log n)

Explanation: On average, the time complexity of the insert function in a hash table is O(1). The condition is that the number of collisions be kept to a minimum.

**11. What is the time complexity of the search function in a hash table using a binary tree?****A) O(1)**

B) O(n)

C) O(log n)

D) O(n log n)

Explanation: The search function in a hash table has an O time complexity (1). The condition is that the number of collisions be kept to a minimum.

A binary tree is a tree data structure in which each node has no more than two members, known as the left and right children. A (non-empty) binary tree is a triangle (L, S, R), where L and R are binary trees or the empty set, and S is a singleton set containing the root, according to a relational description using only set theory notions. The binary tree may also be the empty set, according to some writers. Binary (and K-ary) trees, as described here, are arborescences from the standpoint of graph theory.