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 best-case time complexity of Merge Sort?
A.
O(n)
B.
O(n log n)
C.
O(log n)
D.
O(n^2)
Show solution
Solution
The best-case time complexity of Merge Sort is O(n log n), as it always divides the array regardless of the order.
Correct Answer:
B
— O(n log n)
Learn More →
Q. What is the best-case time complexity of Quick Sort?
A.
O(n)
B.
O(n log n)
C.
O(log n)
D.
O(n^2)
Show solution
Solution
The best-case time complexity of Quick Sort is O(n log n), which occurs when the pivot divides the array into two equal halves.
Correct Answer:
B
— O(n log n)
Learn More →
Q. What is the broadcast address for the subnet 192.168.1.0/24?
A.
192.168.1.255
B.
192.168.1.0
C.
192.168.1.1
D.
192.168.1.254
Show solution
Solution
The broadcast address for the subnet 192.168.1.0/24 is 192.168.1.255, used to send data to all hosts in that subnet.
Correct Answer:
A
— 192.168.1.255
Learn More →
Q. What is the broadcast address for the subnet 192.168.10.0/24?
A.
192.168.10.0
B.
192.168.10.255
C.
192.168.10.1
D.
192.168.10.128
Show solution
Solution
The broadcast address for a /24 subnet is the last address in the range, which is 192.168.10.255.
Correct Answer:
B
— 192.168.10.255
Learn More →
Q. What is the CIDR notation for a subnet mask of 255.255.255.128?
A.
/25
B.
/26
C.
/27
D.
/24
Show solution
Solution
The CIDR notation for a subnet mask of 255.255.255.128 is /25, indicating that the first 25 bits are used for the network.
Correct Answer:
A
— /25
Learn More →
Q. What is the CIDR notation for a subnet mask of 255.255.255.192?
A.
/24
B.
/26
C.
/28
D.
/30
Show solution
Solution
The CIDR notation for a subnet mask of 255.255.255.192 is /26, indicating 26 bits are used for the network part.
Correct Answer:
B
— /26
Learn More →
Q. What is the CIDR notation for a subnet mask of 255.255.255.224?
A.
/24
B.
/25
C.
/26
D.
/27
Show solution
Solution
The subnet mask 255.255.255.224 corresponds to a CIDR notation of /27, which means 27 bits are used for the network part.
Correct Answer:
D
— /27
Learn More →
Q. What is the CIDR notation for a subnet mask of 255.255.255.248?
A.
/24
B.
/25
C.
/26
D.
/29
Show solution
Solution
The subnet mask 255.255.255.248 corresponds to /29, as it has 29 bits set to 1.
Correct Answer:
D
— /29
Learn More →
Q. What is the color property of a Red-Black tree?
A.
Every node is either red or blue.
B.
Every node is either red or black.
C.
Every node is either black or white.
D.
Every node is either green or red.
Show solution
Solution
In a Red-Black tree, each node is colored either red or black, which helps maintain balance during insertions and deletions.
Correct Answer:
B
— Every node is either red or black.
Learn More →
Q. What is the correct syntax to include a header file in C?
A.
#include <header.h>
B.
#include 'header.h'
C.
#include header.h
D.
#include <header>
Show solution
Solution
The correct syntax to include a header file in C is #include <header.h>.
Correct Answer:
A
— #include <header.h>
Learn More →
Q. What is the default port number for HTTP?
Show solution
Solution
The default port number for HTTP is 80.
Correct Answer:
C
— 80
Learn More →
Q. What is the default subnet mask for a Class C IP address?
A.
255.0.0.0
B.
255.255.0.0
C.
255.255.255.0
D.
255.255.255.255
Show solution
Solution
The default subnet mask for a Class C IP address is 255.255.255.0, allowing for 256 addresses in the subnet.
Correct Answer:
C
— 255.255.255.0
Learn More →
Q. What is the difference between 'on-policy' and 'off-policy' learning?
A.
On-policy learns from the current policy, off-policy learns from a different policy
B.
On-policy uses supervised learning, off-policy uses unsupervised learning
C.
On-policy is faster than off-policy
D.
There is no difference
Show solution
Solution
On-policy learning updates the policy based on actions taken by the current policy, while off-policy learning can learn from actions taken by a different policy.
Correct Answer:
A
— On-policy learns from the current policy, off-policy learns from a different policy
Learn More →
Q. What is the effect of adding more features to a linear regression model?
A.
Always improves model performance
B.
Can lead to overfitting
C.
Reduces interpretability
D.
Both B and C
Show solution
Solution
Adding more features can lead to overfitting and reduce the interpretability of the model, especially if the features are not relevant.
Correct Answer:
D
— Both B and C
Learn More →
Q. What is the effect of adding more predictors to a linear regression model?
A.
Always improves model accuracy
B.
Can lead to overfitting
C.
Reduces the complexity of the model
D.
Eliminates multicollinearity
Show solution
Solution
Adding more predictors can lead to overfitting, especially if the additional predictors do not contribute meaningful information.
Correct Answer:
B
— Can lead to overfitting
Learn More →
Q. What is the effect of increasing the number of trees in a Random Forest?
A.
It always increases the training time.
B.
It can improve model accuracy but may lead to diminishing returns.
C.
It decreases the model's interpretability.
D.
It reduces the model's variance but increases bias.
Show solution
Solution
Increasing the number of trees can improve model accuracy due to better averaging, but there are diminishing returns after a certain point.
Correct Answer:
B
— It can improve model accuracy but may lead to diminishing returns.
Learn More →
Q. What is the effect of increasing the regularization parameter (C) in SVM?
A.
Increases the margin width
B.
Decreases the margin width
C.
Increases the number of support vectors
D.
Decreases the number of support vectors
Show solution
Solution
Increasing the regularization parameter (C) decreases the margin width, allowing the model to fit the training data more closely.
Correct Answer:
B
— Decreases the margin width
Learn More →
Q. What is the effect of multicollinearity in a linear regression model?
A.
It improves model accuracy
B.
It makes coefficient estimates unstable
C.
It has no effect on the model
D.
It simplifies the model
Show solution
Solution
Multicollinearity can make coefficient estimates unstable and difficult to interpret in a linear regression model.
Correct Answer:
B
— It makes coefficient estimates unstable
Learn More →
Q. What is the effect of multicollinearity on a linear regression model?
A.
It improves model accuracy
B.
It makes coefficient estimates unstable
C.
It has no effect on the model
D.
It simplifies the model
Show solution
Solution
Multicollinearity makes coefficient estimates unstable, leading to difficulties in interpreting the model.
Correct Answer:
B
— It makes coefficient estimates unstable
Learn More →
Q. What is the effect of outliers on a linear regression model?
A.
They have no effect
B.
They can significantly skew the results
C.
They improve the model's accuracy
D.
They only affect the intercept
Show solution
Solution
Outliers can significantly skew the results of a linear regression model, affecting both the slope and intercept.
Correct Answer:
B
— They can significantly skew the results
Learn More →
Q. What is the effect of outliers on K-means clustering?
A.
They have no effect on the clustering results
B.
They can significantly distort the cluster centroids
C.
They improve the clustering accuracy
D.
They help in determining the number of clusters
Show solution
Solution
Outliers can significantly distort the cluster centroids in K-means clustering, leading to inaccurate clustering results.
Correct Answer:
B
— They can significantly distort the cluster centroids
Learn More →
Q. What is the effect of using a linear kernel in SVM?
A.
It allows for non-linear decision boundaries
B.
It simplifies the model and reduces computation
C.
It increases the risk of overfitting
D.
It can only classify linearly separable data
Show solution
Solution
Using a linear kernel in SVM means that the model can only create linear decision boundaries, making it suitable for linearly separable data.
Correct Answer:
D
— It can only classify linearly separable data
Learn More →
Q. What is the effect of using a soft margin in SVM?
A.
It allows some misclassifications
B.
It increases the model complexity
C.
It reduces the number of support vectors
D.
It guarantees a perfect classification
Show solution
Solution
A soft margin allows for some misclassifications, which can help in achieving better generalization on unseen data.
Correct Answer:
A
— It allows some misclassifications
Learn More →
Q. What is the effect of using a very small value for the regularization parameter 'C' in SVM?
A.
Increased model complexity
B.
Increased margin width
C.
More misclassifications
D.
Decreased training time
Show solution
Solution
A very small value for 'C' allows for a wider margin, potentially leading to more misclassifications but better generalization.
Correct Answer:
B
— Increased margin width
Learn More →
Q. What is the effect of using binary search on a linked list?
A.
Faster than array
B.
Slower than array
C.
Same as array
D.
Not applicable
Show solution
Solution
Binary search is not applicable to linked lists due to their non-contiguous memory allocation.
Correct Answer:
D
— Not applicable
Learn More →
Q. What is the effect of using polynomial features in a linear regression model?
A.
It reduces the model complexity
B.
It can capture non-linear relationships
C.
It increases the risk of underfitting
D.
It eliminates multicollinearity
Show solution
Solution
Polynomial features allow the model to capture non-linear relationships between the features and the target variable.
Correct Answer:
B
— It can capture non-linear relationships
Learn More →
Q. What is the first step in Dijkstra's algorithm?
A.
Select the node with the smallest tentative distance
B.
Initialize all distances to infinity
C.
Mark all nodes as unvisited
D.
Add all edges to the priority queue
Show solution
Solution
The first step is to initialize the distance to the source node as 0 and all other nodes as infinity.
Correct Answer:
B
— Initialize all distances to infinity
Learn More →
Q. What is the first usable IP address in the subnet 10.0.0.0/22?
A.
10.0.0.1
B.
10.0.0.0
C.
10.0.3.255
D.
10.0.0.2
Show solution
Solution
The first usable IP address in the subnet 10.0.0.0/22 is 10.0.0.1, as 10.0.0.0 is the network address.
Correct Answer:
A
— 10.0.0.1
Learn More →
Q. What is the first usable IP address in the subnet 10.0.0.0/24?
A.
10.0.0.0
B.
10.0.0.1
C.
10.0.0.255
D.
10.0.1.0
Show solution
Solution
The first usable IP address in the subnet 10.0.0.0/24 is 10.0.0.1, as 10.0.0.0 is the network address.
Correct Answer:
B
— 10.0.0.1
Learn More →
Q. What is the first valid host address in the subnet 192.168.1.0/24?
A.
192.168.1.0
B.
192.168.1.1
C.
192.168.1.255
D.
192.168.1.254
Show solution
Solution
In the subnet 192.168.1.0/24, the first valid host address is 192.168.1.1, as 192.168.1.0 is the network address.
Correct Answer:
B
— 192.168.1.1
Learn More →
Showing 1051 to 1080 of 3237 (108 Pages)
