Computer Science & IT

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Computer Science & IT MCQ & Objective Questions

Computer Science & IT is a crucial subject for students preparing for school and competitive exams in India. Mastering this field not only enhances your understanding of technology but also significantly boosts your exam scores. Practicing MCQs and objective questions is an effective way to reinforce your knowledge and identify important questions that frequently appear in exams.

What You Will Practise Here

Fundamentals of Computer Science
Data Structures and Algorithms
Operating Systems Concepts
Networking Basics and Protocols
Database Management Systems
Software Engineering Principles
Programming Languages Overview

Exam Relevance

Computer Science & IT is an integral part of the curriculum for CBSE, State Boards, and competitive exams like NEET and JEE. Questions often focus on theoretical concepts, practical applications, and problem-solving skills. Common patterns include multiple-choice questions that test your understanding of key concepts, definitions, and the ability to apply knowledge in various scenarios.

Common Mistakes Students Make

Confusing similar concepts in data structures, such as arrays and linked lists.
Overlooking the importance of algorithms and their time complexities.
Misunderstanding the functions and roles of different operating system components.
Neglecting to practice coding problems, leading to difficulty in programming questions.
Failing to grasp the fundamentals of networking, which can lead to errors in related MCQs.

FAQs

Question: What are the best ways to prepare for Computer Science & IT exams?
Answer: Regular practice of MCQs, understanding key concepts, and reviewing past exam papers are effective strategies.

Question: How can I improve my problem-solving skills in Computer Science?
Answer: Engage in coding exercises, participate in study groups, and tackle a variety of practice questions.

Start your journey towards mastering Computer Science & IT today! Solve our practice MCQs to test your understanding and enhance your exam preparation. Remember, consistent practice is the key to success!

Artificial Intelligence & ML Compiler Design Computer Networks Data Structures & Algorithms Databases Operating Systems Programming & DS Programming Fundamentals Theory of Computation Web Development

Q. What is the time complexity of deleting an element from a linked list when the pointer to the node is given?

A. O(1)
B. O(n)
C. O(log n)
D. O(n log n)

Solution

If you have a pointer to the node to be deleted, the deletion can be done in constant time, O(1).

Correct Answer: A — O(1)

Q. What is the time complexity of deleting an element from a linked list when you have a pointer to that node?

A. O(1)
B. O(n)
C. O(log n)
D. O(n^2)

Solution

If you have a pointer to the node to be deleted, the deletion can be done in constant time, O(1).

Correct Answer: A — O(1)

Q. What is the time complexity of deleting an element from a linked list?

A. O(1)
B. O(n)
C. O(log n)
D. O(n^2)

Solution

The time complexity is O(n) in the worst case, as you may need to traverse the list to find the element to delete.

Correct Answer: B — O(n)

Q. What is the time complexity of deleting an element from a queue implemented using a linked list?

A. O(1)
B. O(n)
C. O(log n)
D. O(n^2)

Solution

Deleting an element from the front of a queue implemented with a linked list is done in constant time, O(1).

Correct Answer: A — O(1)

Q. What is the time complexity of deleting an element from a queue implemented with a linked list?

A. O(1)
B. O(n)
C. O(log n)
D. O(n log n)

Solution

Deleting from the front of a linked list queue is a constant time operation, hence O(1).

Correct Answer: A — O(1)

Q. What is the time complexity of deleting an element from a queue?

A. O(1)
B. O(n)
C. O(log n)
D. O(n^2)

Solution

Deleting an element from the front of a queue is done in constant time, hence O(1).

Correct Answer: A — O(1)

Q. What is the time complexity of deleting an element from a singly linked list when the pointer to the node is given?

A. O(1)
B. O(n)
C. O(log n)
D. O(n^2)

Solution

If you have a pointer to the node to be deleted, the deletion can be done in O(1) time.

Correct Answer: A — O(1)

Q. What is the time complexity of deleting an element from a stack?

A. O(1)
B. O(n)
C. O(log n)
D. O(n^2)

Solution

Deleting an element from a stack (pop operation) is done in constant time, hence O(1).

Correct Answer: A — O(1)

Q. What is the time complexity of deleting the last element from a dynamic array?

A. O(1)
B. O(n)
C. O(log n)
D. O(n^2)

Solution

Deleting the last element from a dynamic array is a constant time operation, so the time complexity is O(1).

Correct Answer: A — O(1)

Q. What is the time complexity of deleting the last element from a singly linked list?

A. O(1)
B. O(n)
C. O(log n)
D. O(n^2)

Solution

To delete the last element from a singly linked list, you must traverse the list to find the second-to-last element, resulting in O(n) time complexity.

Correct Answer: B — O(n)

Q. What is the time complexity of deleting the last node in a singly linked list?

A. O(1)
B. O(n)
C. O(log n)
D. O(n log n)

Solution

To delete the last node in a singly linked list, you must traverse the list to find the second-to-last node, resulting in O(n) time complexity.

Correct Answer: B — O(n)

Q. What is the time complexity of depth-first search (DFS) in a graph?

A. O(V)
B. O(E)
C. O(V + E)
D. O(V^2)

Solution

DFS visits each vertex and edge once, leading to a time complexity of O(V + E), where V is vertices and E is edges.

Correct Answer: C — O(V + E)

Q. What is the time complexity of depth-first search (DFS) on a graph?

A. O(V)
B. O(E)
C. O(V + E)
D. O(V * E)

Solution

DFS explores all vertices (V) and edges (E) in the graph, leading to a time complexity of O(V + E).

Correct Answer: C — O(V + E)

Q. What is the time complexity of dequeuing an element from a queue implemented using an array?

A. O(1)
B. O(n)
C. O(log n)
D. O(n^2)

Solution

Dequeuing an element from a queue implemented using an array can take O(n) time if all elements need to be shifted after removing the front element.

Correct Answer: B — O(n)

Q. What is the time complexity of dequeuing an element from a queue implemented using a circular array?

A. O(1)
B. O(n)
C. O(log n)
D. O(n^2)

Solution

Dequeuing an element from a queue implemented using a circular array can be done in constant time, O(1), as it involves adjusting the front index.

Correct Answer: A — O(1)

Q. What is the time complexity of dequeuing an element from a queue implemented using a linked list?

A. O(1)
B. O(n)
C. O(log n)
D. O(n log n)

Solution

Dequeuing from a queue implemented with a linked list is O(1) as it involves removing the head node.

Correct Answer: A — O(1)

Q. What is the time complexity of Dijkstra's algorithm using a binary heap?

A. O(V^2)
B. O(E log V)
C. O(V log V)
D. O(E + V)

Solution

The time complexity of Dijkstra's algorithm using a binary heap is O(E log V), where E is the number of edges and V is the number of vertices.

Correct Answer: B — O(E log V)

Q. What is the time complexity of Dijkstra's algorithm using a priority queue implemented with a binary heap?

A. O(V^2)
B. O(E log V)
C. O(V log V)
D. O(E + V)

Solution

Dijkstra's algorithm has a time complexity of O(E log V) when using a priority queue implemented with a binary heap, where E is the number of edges and V is the number of vertices.

Correct Answer: B — O(E log V)

Q. What is the time complexity of Dijkstra's algorithm using a priority queue?

A. O(V^2)
B. O(E + V log V)
C. O(V log V)
D. O(E log V)

Solution

Dijkstra's algorithm has a time complexity of O(E log V) when implemented with a priority queue.

Correct Answer: D — O(E log V)

Q. What is the time complexity of Dijkstra's algorithm when implemented with a binary heap?

A. O(V^2)
B. O(E log V)
C. O(V log V)
D. O(E + V)

Solution

When using a binary heap, the time complexity of Dijkstra's algorithm is O(E log V), where E is the number of edges and V is the number of vertices.

Correct Answer: B — O(E log V)

Q. What is the time complexity of Dijkstra's algorithm when using a binary heap?

A. O(V^2)
B. O(E log V)
C. O(V log V)
D. O(E + V)

Solution

When implemented with a binary heap, the time complexity of Dijkstra's algorithm is O(E log V), where E is the number of edges and V is the number of vertices.

Correct Answer: B — O(E log V)

Q. What is the time complexity of Dijkstra's algorithm when using a priority queue implemented with a binary heap?

A. O(V^2)
B. O(E log V)
C. O(V log V)
D. O(E + V)

Solution

The time complexity of Dijkstra's algorithm using a binary heap is O(E log V), where E is the number of edges and V is the number of vertices.

Correct Answer: B — O(E log V)

Q. What is the time complexity of enqueue and dequeue operations in a queue implemented using a linked list?

A. O(1)
B. O(n)
C. O(log n)
D. O(n log n)

Solution

Both enqueue and dequeue operations can be performed in constant time O(1) in a linked list implementation.

Correct Answer: A — O(1)

Q. What is the time complexity of enqueue and dequeue operations in a queue implemented with a linked list?

A. O(1)
B. O(n)
C. O(log n)
D. O(n log n)

Solution

Both enqueue and dequeue operations can be performed in constant time, O(1), when using a linked list.

Correct Answer: A — O(1)

Q. What is the time complexity of enqueue and dequeue operations in a standard queue implemented using a linked list?

A. O(1)
B. O(n)
C. O(log n)
D. O(n log n)

Solution

Both enqueue and dequeue operations in a queue implemented using a linked list have a time complexity of O(1).

Correct Answer: A — O(1)

Q. What is the time complexity of enqueueing an element in a queue implemented using an array?

A. O(1)
B. O(n)
C. O(log n)
D. O(n^2)

Solution

Enqueueing an element in a queue implemented using an array can be done in constant time, O(1), if there is space available.

Correct Answer: A — O(1)

Q. What is the time complexity of enqueueing an element in a queue implemented using a linked list?

A. O(1)
B. O(n)
C. O(log n)
D. O(n log n)

Solution

Enqueueing an element in a queue implemented with a linked list is done in constant time, O(1), as it involves adding to the tail of the list.

Correct Answer: A — O(1)

Q. What is the time complexity of enqueueing an element in a queue implemented with a linked list?

A. O(1)
B. O(n)
C. O(log n)
D. O(n log n)

Solution

Enqueueing an element in a queue implemented with a linked list is done in constant time, O(1), by adding the element to the end of the list.

Correct Answer: A — O(1)

Q. What is the time complexity of enqueueing an element in a queue?

A. O(1)
B. O(n)
C. O(log n)
D. O(n^2)

Solution

Enqueueing an element in a queue is done in constant time, hence O(1).

Correct Answer: A — O(1)

Q. What is the time complexity of enqueuing an element in a queue implemented using an array?

A. O(1)
B. O(n)
C. O(log n)
D. O(n^2)

Solution

Enqueuing an element in a queue implemented using an array is done in constant time, O(1), unless the array needs to be resized.

Correct Answer: A — O(1)

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