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!

Q. In an AVL tree, what must be done after an insertion if the tree becomes unbalanced?
  • A. Perform a single rotation
  • B. Perform a double rotation
  • C. Rebuild the entire tree
  • D. Nothing is needed
Q. In an AVL tree, what operation is performed when a node becomes unbalanced after an insertion?
  • A. Rotation
  • B. Traversal
  • C. Deletion
  • D. Rebalancing
Q. In an LR parser, what is the purpose of the 'shift' action?
  • A. To reduce a production.
  • B. To push a state onto the stack.
  • C. To pop a state from the stack.
  • D. To accept the input.
Q. In BFS, which node is visited first?
  • A. The deepest node
  • B. The first node added to the queue
  • C. The last node added to the queue
  • D. The parent node
Q. In binary search, how do you calculate the middle index?
  • A. (low + high) / 2
  • B. (low + high) / 2 + 1
  • C. (low + high) / 2 - 1
  • D. low + (high - low) / 2
Q. In binary search, if the target is less than the middle element, what should be the next step?
  • A. Search the right half
  • B. Search the left half
  • C. Return the middle element
  • D. Increase the middle index
Q. In binary search, if the target value is not found, what will be the return value?
  • A. -1
  • B. 0
  • C. null
  • D. the index of the closest value
Q. In binary search, what happens if the middle element is greater than the target?
  • A. Search the left half
  • B. Search the right half
  • C. Search both halves
  • D. Return the middle element
Q. In binary search, what happens to the search space after each comparison?
  • A. It doubles
  • B. It halves
  • C. It remains the same
  • D. It increases linearly
Q. In binary search, what is the formula to find the middle index?
  • A. (low + high) / 2
  • B. (low + high) / 2 + 1
  • C. (low + high) / 2 - 1
  • D. low + high
Q. In binary search, what is the purpose of calculating the mid index?
  • A. To find the maximum element
  • B. To divide the array into two halves
  • C. To check for duplicates
  • D. To sort the array
Q. In CIDR notation, what does /16 signify?
  • A. 255.255.0.0 subnet mask
  • B. 65,536 possible addresses
  • C. A Class B network
  • D. All of the above
Q. In CIDR notation, what does /24 represent?
  • A. 255.255.255.0 subnet mask
  • B. 256 IP addresses
  • C. 24 hosts per subnet
  • D. 24 bits for the host portion
Q. In CIDR notation, what does a /22 subnet mask indicate?
  • A. 255.255.252.0
  • B. 255.255.255.0
  • C. 255.255.255.252
  • D. 255.255.255.128
Q. In CIDR notation, what does a /24 subnet indicate?
  • A. 255.255.255.0
  • B. 255.255.0.0
  • C. 255.0.0.0
  • D. 255.255.255.255
Q. In CIDR notation, what does a /24 subnet mask represent?
  • A. 255.255.255.0
  • B. 255.255.0.0
  • C. 255.0.0.0
  • D. 255.255.255.255
Q. In classification problems, what does the F1 Score represent?
  • A. The harmonic mean of precision and recall
  • B. The average of precision and recall
  • C. The total number of true positives
  • D. The ratio of true positives to total predictions
Q. In classification problems, what does the term 'class label' refer to?
  • A. The input features of the data
  • B. The predicted output category
  • C. The algorithm used for training
  • D. The evaluation metric
Q. In classification tasks, what does precision measure?
  • A. True positives over total positives
  • B. True positives over total predicted positives
  • C. True positives over total actual positives
  • D. True negatives over total negatives
Q. In classification tasks, what does the F1 Score represent?
  • A. The harmonic mean of precision and recall
  • B. The average of precision and recall
  • C. The total number of true positives
  • D. The ratio of true positives to total predictions
Q. In DBSCAN, what does the term 'epsilon' refer to?
  • A. The minimum number of points required to form a cluster
  • B. The maximum distance between two points to be considered in the same cluster
  • C. The number of clusters to form
  • D. The density of the clusters
Q. In Decision Trees, what does the Gini impurity measure?
  • A. The accuracy of the model
  • B. The purity of a node
  • C. The depth of the tree
  • D. The number of features used
Q. In Depth-First Search (DFS), which data structure is primarily used to keep track of the vertices to be explored?
  • A. Queue
  • B. Stack
  • C. Array
  • D. Linked List
Q. In Depth-First Search (DFS), which data structure is primarily used?
  • A. Queue
  • B. Stack
  • C. Array
  • D. Hash Table
Q. In DFS, what is the maximum depth of recursion for a graph with V vertices?
  • A. O(V)
  • B. O(E)
  • C. O(V + E)
  • D. O(log V)
Q. In DFS, what is the primary data structure used?
  • A. Queue
  • B. Stack
  • C. Array
  • D. Hash Table
Q. In Dijkstra's algorithm, how is the next node to process selected?
  • A. By selecting the node with the highest degree
  • B. By selecting the node with the lowest tentative distance
  • C. By selecting the node that was added last
  • D. By selecting a random node
Q. In Dijkstra's algorithm, what condition must be met for a vertex to be added to the set of visited vertices?
  • A. It must have the smallest edge weight
  • B. It must be the last vertex processed
  • C. It must be connected to the source
  • D. It must have the highest degree
Q. In Dijkstra's algorithm, what data structure is commonly used to keep track of the minimum distance to each vertex?
  • A. Array
  • B. Stack
  • C. Priority Queue
  • D. Linked List
Q. In Dijkstra's algorithm, what data structure is commonly used to keep track of the nodes to be explored?
  • A. Array
  • B. Stack
  • C. Priority Queue
  • D. Linked List
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