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!
Q. What is the time complexity of the quicksort algorithm in the worst case?
A.
O(n)
B.
O(n log n)
C.
O(n^2)
D.
O(log n)
Show solution
Solution
In the worst case, quicksort can degrade to O(n^2) time complexity, typically when the pivot is the smallest or largest element.
Correct Answer:
C
— O(n^2)
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Q. What is the time complexity of the worst-case scenario for Quick Sort when the pivot is the smallest or largest element?
A.
O(n)
B.
O(n log n)
C.
O(n^2)
D.
O(log n)
Show solution
Solution
The worst-case time complexity for Quick Sort occurs when the pivot is the smallest or largest element, resulting in O(n^2).
Correct Answer:
C
— O(n^2)
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Q. What is the time complexity of traversing a binary tree using in-order traversal?
A.
O(n)
B.
O(log n)
C.
O(n log n)
D.
O(1)
Show solution
Solution
In-order traversal visits each node exactly once, resulting in a time complexity of O(n), where n is the number of nodes in the tree.
Correct Answer:
A
— O(n)
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Q. What is the time complexity of traversing a binary tree with n nodes?
A.
O(n)
B.
O(log n)
C.
O(n log n)
D.
O(1)
Show solution
Solution
Traversing a binary tree requires visiting each node once, leading to a time complexity of O(n).
Correct Answer:
A
— O(n)
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Q. What is the time complexity of traversing a binary tree?
A.
O(n)
B.
O(log n)
C.
O(n log n)
D.
O(1)
Show solution
Solution
Traversing a binary tree requires visiting each node once, leading to a time complexity of O(n).
Correct Answer:
A
— O(n)
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Q. What is the time complexity of traversing a linked list with 'n' nodes?
A.
O(1)
B.
O(n)
C.
O(log n)
D.
O(n^2)
Show solution
Solution
Traversing a linked list requires visiting each node, leading to a time complexity of O(n).
Correct Answer:
B
— O(n)
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Q. What is the total number of hosts in a subnet with a /18 subnet mask?
A.
16382
B.
16384
C.
8190
D.
8192
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Solution
A /18 subnet mask allows for 2^(32-18) = 16384 total addresses, of which 16382 are usable for hosts.
Correct Answer:
B
— 16384
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Q. What is the typical output of the intermediate code generation phase?
A.
Source code
B.
Assembly code
C.
Intermediate representation
D.
Executable code
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Solution
The output of the intermediate code generation phase is typically an intermediate representation that can be further optimized and translated into machine code.
Correct Answer:
C
— Intermediate representation
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Q. What is the worst-case number of comparisons in binary search for an array of size 16?
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Solution
The worst-case number of comparisons is log2(16) = 4, but since we start counting from 0, it takes 5 comparisons.
Correct Answer:
C
— 6
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Q. What is the worst-case scenario for binary search?
A.
Finding the first element
B.
Finding the last element
C.
Finding an element not in the array
D.
Finding the middle element
Show solution
Solution
In the worst case, binary search will check all levels of the tree, which is O(log n), but it will not find the element.
Correct Answer:
C
— Finding an element not in the array
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Q. What is the worst-case scenario for the number of comparisons in binary search on an array of size n?
A.
n
B.
log n
C.
n log n
D.
1
Show solution
Solution
In the worst case, binary search makes log n comparisons to find the target or determine its absence.
Correct Answer:
B
— log n
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Q. What is the worst-case scenario for the number of comparisons in binary search?
A.
n
B.
log n
C.
n log n
D.
1
Show solution
Solution
In the worst case, binary search will make log n comparisons, where n is the number of elements in the array.
Correct Answer:
B
— log n
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Q. What is the worst-case scenario for the number of comparisons made by binary search?
A.
n
B.
log n
C.
n log n
D.
1
Show solution
Solution
In the worst case, binary search makes log n comparisons, where n is the number of elements in the array.
Correct Answer:
B
— log n
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Q. What is the worst-case scenario for the number of comparisons made by binary search on an array of size n?
A.
n
B.
log n
C.
n log n
D.
1
Show solution
Solution
In the worst case, binary search makes log n comparisons, where n is the number of elements in the array.
Correct Answer:
B
— log n
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Q. What is the worst-case scenario for the number of iterations in binary search?
A.
O(n)
B.
O(log n)
C.
O(n log n)
D.
O(1)
Show solution
Solution
The worst-case scenario for binary search is O(log n), as it halves the search space with each iteration.
Correct Answer:
B
— O(log n)
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Q. What is the worst-case time complexity for accessing an element in a queue implemented using a linked list?
A.
O(1)
B.
O(n)
C.
O(log n)
D.
O(n^2)
Show solution
Solution
Accessing an element in a queue implemented using a linked list has a worst-case time complexity of O(n) because you may need to traverse the list.
Correct Answer:
B
— O(n)
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Q. What is the worst-case time complexity for balancing an AVL tree after insertion?
A.
O(n)
B.
O(log n)
C.
O(n log n)
D.
O(1)
Show solution
Solution
The worst-case time complexity for balancing an AVL tree after insertion is O(log n).
Correct Answer:
B
— O(log n)
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Q. What is the worst-case time complexity for bubble sort?
A.
O(n)
B.
O(n log n)
C.
O(n^2)
D.
O(log n)
Show solution
Solution
The worst-case time complexity for bubble sort occurs when the array is sorted in reverse order, resulting in O(n^2).
Correct Answer:
C
— O(n^2)
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Q. What is the worst-case time complexity for deleting a node from a Red-Black tree?
A.
O(n)
B.
O(log n)
C.
O(n log n)
D.
O(1)
Show solution
Solution
The worst-case time complexity for deleting a node from a Red-Black tree is O(log n) due to its balanced structure.
Correct Answer:
B
— O(log n)
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Q. What is the worst-case time complexity for deleting a node from an AVL tree?
A.
O(n)
B.
O(log n)
C.
O(n log n)
D.
O(1)
Show solution
Solution
The worst-case time complexity for deleting a node from an AVL tree is O(log n) due to the need to maintain balance.
Correct Answer:
B
— O(log n)
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Q. What is the worst-case time complexity for deleting a node in an AVL tree?
A.
O(1)
B.
O(log n)
C.
O(n)
D.
O(n log n)
Show solution
Solution
The worst-case time complexity for deleting a node in an AVL tree is O(log n) due to the need to maintain balance.
Correct Answer:
B
— O(log n)
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Q. What is the worst-case time complexity for deleting an element from an AVL tree?
A.
O(1)
B.
O(log n)
C.
O(n)
D.
O(n log n)
Show solution
Solution
The worst-case time complexity for deleting an element from an AVL tree is O(log n) due to the need to maintain balance.
Correct Answer:
B
— O(log n)
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Q. What is the worst-case time complexity for deletion in an AVL tree?
A.
O(n)
B.
O(log n)
C.
O(n log n)
D.
O(1)
Show solution
Solution
The worst-case time complexity for deletion in an AVL tree is O(log n) due to the tree's balanced structure.
Correct Answer:
B
— O(log n)
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Q. What is the worst-case time complexity for 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^2)
Show solution
Solution
Both enqueue and dequeue operations can be performed in constant time, O(1), when using a linked list.
Correct Answer:
A
— O(1)
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Q. What is the worst-case time complexity for inserting a node in a binary search tree?
A.
O(n)
B.
O(log n)
C.
O(n log n)
D.
O(1)
Show solution
Solution
In the worst case, if the tree is unbalanced (like a linked list), the time complexity for insertion can be O(n).
Correct Answer:
A
— O(n)
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Q. What is the worst-case time complexity for inserting a node in an AVL tree?
A.
O(n)
B.
O(log n)
C.
O(n log n)
D.
O(1)
Show solution
Solution
The worst-case time complexity for inserting a node in an AVL tree is O(log n) due to the tree's balanced nature.
Correct Answer:
B
— O(log n)
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Q. What is the worst-case time complexity for inserting an element at the beginning of a singly linked list?
A.
O(1)
B.
O(n)
C.
O(log n)
D.
O(n log n)
Show solution
Solution
Inserting at the beginning of a singly linked list is a constant time operation, O(1).
Correct Answer:
A
— O(1)
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Q. What is the worst-case time complexity for inserting an element in a binary search tree?
A.
O(log n)
B.
O(n)
C.
O(n log n)
D.
O(1)
Show solution
Solution
The worst-case time complexity for inserting an element in a binary search tree is O(n), which occurs when the tree is unbalanced.
Correct Answer:
B
— O(n)
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Q. What is the worst-case time complexity for inserting an element in an unbalanced binary tree?
A.
O(log n)
B.
O(n)
C.
O(n log n)
D.
O(1)
Show solution
Solution
The worst-case time complexity for inserting an element in an unbalanced binary tree is O(n), when the tree becomes a linear chain.
Correct Answer:
B
— O(n)
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Q. What is the worst-case time complexity for inserting an element into a binary search tree?
A.
O(1)
B.
O(log n)
C.
O(n)
D.
O(n log n)
Show solution
Solution
In the worst case, a binary search tree can become unbalanced (like a linked list), leading to a time complexity of O(n) for insertion.
Correct Answer:
C
— O(n)
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