Free Mock Test : Data Structures and Algorithms : Hashing and Heap (Test 1)

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Free Mock Test - Data Structures and Algorithms : Hashing and Heap (Test 1)

In an effort to support computer science students, coding enthusiasts, and job seekers preparing for technical interviews, a comprehensive Free Online Data Structure Mock Test has been launched. The test is designed to help learners evaluate their understanding of fundamental and advanced data structure concepts through a structured and interactive assessment.
Data Structures form the backbone of computer science and software development. Topics such as Arrays, Linked Lists, Stacks, Queues, Trees, Graphs, Hashing, and Algorithms are frequently asked in academic examinations, coding competitions, and technical interviews conducted by leading technology companies.
The newly introduced mock test platform offers a wide range of multiple-choice questions (MCQs) covering beginner, intermediate, and advanced-level topics. Participants can assess their strengths and identify areas requiring further improvement through instant results and detailed explanations.

Total Questions : 20

Timer : sec

Question : What is the primary purpose of hashing?

Sorting data

Searching data quickly

Compressing data

Encrypting data

Question : Which data structure is mainly used with hashing?

Stack

Queue

Hash Table

Tree

Question : A good hash function should:

Produce the same output for every key

Minimize collisions

Sort the keys

Increase memory usage

Question : Which collision resolution technique stores collided elements in linked lists?

Linear Probing

Quadratic Probing

Separate Chaining

Double Hashing

Question : Which probing technique checks the next slot sequentially?

Linear Probing

Quadratic Probing

Double Hashing

Chaining

Question : What is the average search complexity in a hash table?

O(n)

O(log n)

O(1)

O(n²)

Question : Which data structure follows the Complete Binary Tree property?

BST

Heap

AVL Tree

Trie

Question : In a Max Heap, the root contains:

Minimum element

Median element

Maximum element

Random element

Question : In a Min Heap, every parent is:

Smaller than or equal to its children

Larger than its children

Equal to all nodes

Randomly arranged

Question : Heap Sort has worst-case complexity of:

O(n)

O(log n)

O(n log n)

O(n²)

Question : What is the worst-case search complexity in a hash table?

O(1)

O(log n)

O(n)

O(n log n)

Question : Which of the following is NOT a collision resolution method?

Linear Probing

Quadratic Probing

Chaining

Bubble Sort

Question : A Binomial Heap is mainly used because:

It supports efficient heap merging

It sorts arrays

It compresses files

It stores graphs

Question : The merge operation in a Binomial Heap takes:

O(n²)

O(log n)

O(1)

O(n)

Question : Fibonacci Heap improves upon Binomial Heap mainly for:

Insert operation

Decrease-Key operation

Searching

Sorting

Question : Which graph algorithm benefits most from Fibonacci Heap?

Bubble Sort

DFS

Dijkstra's Algorithm

Binary Search

Question : Which operation in a Fibonacci Heap has amortized O(1) complexity?

Delete-Min

Insert

Extract-Min

Merge Sort

Question : Which heap has the best amortized complexity for Merge (Union)?

Binary Heap

Binomial Heap

Fibonacci Heap

BST

Question : Which of the following is true about load factor (α) in hashing?

α = Number of Buckets / Number of Elements

α = Number of Elements / Number of Buckets

α is always 1

α is unrelated to collisions

Question : Which statement correctly compares Binomial Heap and Fibonacci Heap?

Binomial Heap has faster decrease-key.

Fibonacci Heap has better amortized decrease-key complexity.

Binomial Heap always has O(1) merge.

Both are identical in performance.

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