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. If you have a sorted array of 1000 elements, how many iterations will binary search take to find an element?
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Solution
Binary search will take log2(1000) which is approximately 9.97, so it will take at most 10 iterations.
Correct Answer:
B
— 9
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Q. If you have a sorted array of 1000 elements, how many iterations will binary search take at most?
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Solution
Binary search will take at most log2(1000) which is approximately 10 iterations.
Correct Answer:
A
— 10
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Q. In a /16 subnet, what is the range of valid host addresses for the network 172.16.0.0?
A.
172.16.0.1 to 172.16.255.254
B.
172.16.0.0 to 172.16.255.255
C.
172.16.0.0 to 172.16.0.255
D.
172.16.1.0 to 172.16.1.255
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Solution
In a /16 subnet, the valid host range is from 172.16.0.1 to 172.16.255.254, with 172.16.0.0 as the network address and 172.16.255.255 as the broadcast address.
Correct Answer:
A
— 172.16.0.1 to 172.16.255.254
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Q. In a binary classification problem using SVM, what does a decision boundary represent?
A.
The line that separates the two classes
B.
The average of all data points
C.
The centroid of the data points
D.
The area of overlap between classes
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Solution
The decision boundary in SVM represents the hyperplane that separates the two classes in the feature space.
Correct Answer:
A
— The line that separates the two classes
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Q. In a binary classification problem, what does a confusion matrix represent?
A.
The relationship between features
B.
The performance of the model on training data
C.
The true positive, false positive, true negative, and false negative counts
D.
The distribution of the target variable
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Solution
A confusion matrix summarizes the performance of a classification model by showing the counts of true positives, false positives, true negatives, and false negatives.
Correct Answer:
C
— The true positive, false positive, true negative, and false negative counts
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Q. In a binary classification problem, what does a high precision indicate?
A.
High true positive rate
B.
Low false positive rate
C.
High true negative rate
D.
Low false negative rate
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Solution
High precision indicates that when the model predicts a positive class, it is correct most of the time, meaning low false positives.
Correct Answer:
B
— Low false positive rate
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Q. In a binary classification problem, what does a high recall indicate?
A.
High true positive rate
B.
High false positive rate
C.
Low true negative rate
D.
Low false negative rate
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Solution
High recall indicates that the model correctly identifies a large proportion of actual positive cases.
Correct Answer:
A
— High true positive rate
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Q. In a binary classification problem, what does a high value of the margin indicate?
A.
The model is likely to overfit
B.
The model has a high bias
C.
The model is more robust to noise
D.
The model is underfitting
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Solution
A high value of the margin indicates that the model is more robust to noise and is likely to generalize better.
Correct Answer:
C
— The model is more robust to noise
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Q. In a binary classification, what does a high recall indicate?
A.
The model is good at identifying negative cases
B.
The model is good at identifying positive cases
C.
The model has a high number of false positives
D.
The model has a high number of false negatives
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Solution
High recall indicates that the model is effective at identifying most of the actual positive cases.
Correct Answer:
B
— The model is good at identifying positive cases
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Q. In a binary search algorithm, if the middle element is greater than the target, what should be done next?
A.
Search the left half
B.
Search the right half
C.
Return the middle element
D.
Increase the middle index
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Solution
If the middle element is greater than the target, the search continues in the left half of the array.
Correct Answer:
A
— Search the left half
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Q. In a binary search algorithm, if the target is less than the mid element, what should be the next step?
A.
Search the right half
B.
Search the left half
C.
Return the mid index
D.
Increase the mid index
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Solution
If the target is less than the mid element, the search should continue in the left half of the array.
Correct Answer:
B
— Search the left half
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Q. In a binary search algorithm, if the target is less than the mid value, what should be the next step?
A.
Search the left half of the array
B.
Search the right half of the array
C.
Return the mid index
D.
Increase the mid index
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Solution
If the target is less than the mid value, the next step is to search the left half of the array.
Correct Answer:
A
— Search the left half of the array
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Q. In a binary search algorithm, what happens if the middle element is equal to the target?
A.
Search continues in the left half
B.
Search continues in the right half
C.
Target is found
D.
Search terminates immediately
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Solution
If the middle element is equal to the target, the search is successful and the target is found.
Correct Answer:
C
— Target is found
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Q. In a binary search algorithm, what happens if the middle element is less than the target?
A.
Search the left half
B.
Search the right half
C.
Return the middle element
D.
Terminate the search
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Solution
If the middle element is less than the target, the search continues in the right half of the array.
Correct Answer:
B
— Search the right half
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Q. In a binary search algorithm, what happens if the target is less than the mid value?
A.
Search the right half
B.
Search the left half
C.
Return the mid index
D.
Increase the mid index
Show solution
Solution
If the target is less than the mid value, the search continues in the left half of the array.
Correct Answer:
B
— Search the left half
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Q. In a binary search algorithm, what happens if the target is less than the middle element?
A.
Search the right half
B.
Search the left half
C.
Return the middle element
D.
End the search
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Solution
If the target is less than the middle element, the search continues in the left half of the array.
Correct Answer:
B
— Search the left half
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Q. In a binary search algorithm, what happens to the search space after each comparison?
A.
It doubles
B.
It remains the same
C.
It halves
D.
It increases linearly
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Solution
After each comparison in binary search, the search space is halved, which is why it is efficient.
Correct Answer:
C
— It halves
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Q. In a binary search implementation, if the target is less than the mid value, what should be the next step?
A.
Search the right half
B.
Search the left half
C.
Return the mid index
D.
Increase the mid index
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Solution
If the target is less than the mid value, the search should continue in the left half of the array.
Correct Answer:
B
— Search the left half
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Q. In a binary search implementation, what condition is checked to determine if the search should continue?
A.
If the target is less than the middle element
B.
If the target is greater than the middle element
C.
If the target is equal to the middle element
D.
All of the above
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Solution
All these conditions are checked to decide whether to continue searching in the left half, right half, or if the target is found.
Correct Answer:
D
— All of the above
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Q. In a binary search implementation, what happens if the target is less than the mid value?
A.
Search the right half
B.
Search the left half
C.
Return mid
D.
End the search
Show solution
Solution
If the target is less than the mid value, the search continues in the left half of the array.
Correct Answer:
B
— Search the left half
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Q. In a binary search implementation, what is the condition to continue searching?
A.
left <= right
B.
left < right
C.
left < mid
D.
mid < right
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Solution
The search continues as long as the left index is less than or equal to the right index.
Correct Answer:
A
— left <= right
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Q. In a binary search implementation, what is the purpose of the 'mid' variable?
A.
To store the maximum value
B.
To find the middle index
C.
To count iterations
D.
To store the minimum value
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Solution
'mid' is used to find the middle index of the current search range to compare with the target value.
Correct Answer:
B
— To find the middle index
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Q. In a binary search implementation, what is the role of the 'low' and 'high' variables?
A.
To store the size of the array
B.
To track the current search range
C.
To count the number of iterations
D.
To store the target value
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Solution
'low' and 'high' define the current range of indices being searched in the array.
Correct Answer:
B
— To track the current search range
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Q. In a binary search tree (BST), how does binary search differ from searching in a sorted array?
A.
It is slower
B.
It requires more comparisons
C.
It can be done in O(1)
D.
It uses tree properties
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Solution
In a binary search tree, the search leverages the tree structure, allowing for efficient searching based on the properties of BSTs.
Correct Answer:
D
— It uses tree properties
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Q. In a binary search tree, how does binary search help in finding an element?
A.
By traversing all nodes
B.
By comparing with the root and deciding left or right
C.
By using a queue
D.
By using a stack
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Solution
In a binary search tree, binary search helps by comparing the target with the root and deciding whether to go left or right based on the value.
Correct Answer:
B
— By comparing with the root and deciding left or right
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Q. In a binary search tree, what is the average time complexity for searching an element?
A.
O(1)
B.
O(log n)
C.
O(n)
D.
O(n log n)
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Solution
The average time complexity for searching an element in a balanced binary search tree is O(log n).
Correct Answer:
B
— O(log n)
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Q. In a binary search tree, what is the maximum number of nodes at depth 'd'?
A.
2^d
B.
2^(d+1) - 1
C.
d^2
D.
d!
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Solution
In a binary search tree, the maximum number of nodes at depth 'd' is 2^d, as each node can have two children.
Correct Answer:
A
— 2^d
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Q. In a binary search tree, what is the time complexity for inserting an element in the average case?
A.
O(1)
B.
O(log n)
C.
O(n)
D.
O(n log n)
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Solution
In a balanced binary search tree, the average-case time complexity for insertion is O(log n).
Correct Answer:
B
— O(log n)
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Q. In a binary search tree, what is the time complexity for searching for an element in the average case?
A.
O(1)
B.
O(n)
C.
O(log n)
D.
O(n log n)
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Solution
In a balanced binary search tree, the average time complexity for searching an element is O(log n).
Correct Answer:
C
— O(log n)
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Q. In a binary search tree, what is the time complexity of searching for an element in the average case?
A.
O(1)
B.
O(log n)
C.
O(n)
D.
O(n log n)
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Solution
In a balanced binary search tree, the average time complexity for searching an element is O(log n).
Correct Answer:
B
— O(log n)
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