Programming & DS MCQ & Objective Questions
Understanding Programming and Data Structures (DS) is crucial for students aiming to excel in their exams. Mastering these concepts not only enhances problem-solving skills but also boosts confidence during assessments. Practicing MCQs and objective questions is an effective way to prepare, as it helps in identifying important questions and reinforces learning through repetition. With targeted practice questions, students can significantly improve their exam performance.
What You Will Practise Here
Fundamentals of Programming Languages
Data Types and Variables
Control Structures: Loops and Conditionals
Functions and Recursion
Arrays and Strings
Data Structures: Stacks, Queues, and Linked Lists
Algorithm Complexity and Big O Notation
Exam Relevance
Programming and Data Structures are integral parts of the curriculum for CBSE, State Boards, and competitive exams like NEET and JEE. Questions often focus on the application of concepts in problem-solving scenarios. Common patterns include multiple-choice questions that test theoretical knowledge, practical applications, and the ability to analyze code snippets. Familiarity with these question types can greatly enhance your exam readiness.
Common Mistakes Students Make
Confusing different data structures and their use cases.
Overlooking edge cases in algorithm design.
Misunderstanding recursion and its base cases.
Neglecting to analyze time and space complexity.
Failing to apply control structures correctly in coding problems.
FAQs
Question: What are the best ways to prepare for Programming & DS MCQs?Answer: Regular practice with objective questions and understanding core concepts through examples is key to mastering this subject.
Question: How can I improve my speed in solving Programming & DS questions?Answer: Timed practice sessions and familiarizing yourself with common question patterns can help improve your speed and accuracy.
Start your journey towards mastering Programming and Data Structures today! Solve practice MCQs to test your understanding and build a strong foundation for your exams. Remember, consistent practice is the key to success!
Q. What is the output of the following code: printf("%d", 5 + 10 * 2);?
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Solution
The output is 25 because of operator precedence: 10 * 2 is evaluated first, then 5 is added.
Correct Answer:
C
— 15
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Q. What is the purpose of the 'free' function in C?
A.
To allocate memory
B.
To release allocated memory
C.
To initialize a pointer
D.
To check memory usage
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Solution
'free' is used to release memory that was previously allocated with 'malloc' or similar functions.
Correct Answer:
B
— To release allocated memory
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Q. What is the purpose of the 'return' statement in a function?
A.
To end the program
B.
To return a value from a function
C.
To declare a variable
D.
To create a loop
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Solution
The 'return' statement is used to return a value from a function to the caller.
Correct Answer:
B
— To return a value from a function
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Q. What is the result of dereferencing a null pointer?
A.
It returns zero
B.
It causes a segmentation fault
C.
It returns a random value
D.
It is valid and returns a pointer
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Solution
Dereferencing a null pointer causes a segmentation fault, as it attempts to access an invalid memory location.
Correct Answer:
B
— It causes a segmentation fault
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Q. What is the size of a pointer on a 64-bit system?
A.
2 bytes
B.
4 bytes
C.
8 bytes
D.
16 bytes
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Solution
On a 64-bit system, the size of a pointer is typically 8 bytes, as it needs to store a 64-bit memory address.
Correct Answer:
C
— 8 bytes
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Q. What is the space complexity of a recursive function that uses O(n) space for its call stack?
A.
O(1)
B.
O(n)
C.
O(n^2)
D.
O(log n)
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Solution
The space complexity of a recursive function that uses O(n) space for its call stack is O(n).
Correct Answer:
B
— O(n)
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Q. What is the time complexity of a recursive function that divides the problem size by half at each step?
A.
O(n)
B.
O(log n)
C.
O(n log n)
D.
O(2^n)
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Solution
The time complexity is O(log n) because the problem size is halved at each recursive call.
Correct Answer:
B
— O(log n)
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Q. What is the time complexity of an in-order traversal of a binary tree?
A.
O(n)
B.
O(log n)
C.
O(n log n)
D.
O(1)
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Solution
In-order traversal visits each node exactly once, resulting in a time complexity of O(n).
Correct Answer:
A
— O(n)
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Q. What is the time complexity of Prim's algorithm for finding the minimum spanning tree using an adjacency matrix?
A.
O(V^2)
B.
O(E log V)
C.
O(V + E)
D.
O(V^3)
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Solution
Prim's algorithm has a time complexity of O(V^2) when using an adjacency matrix.
Correct Answer:
A
— O(V^2)
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Q. What will be the output of the following code: 'for i in range(3): print(i)'?
A.
0 1 2
B.
1 2 3
C.
0 1 2 3
D.
3
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Solution
The loop iterates from 0 to 2, so the output will be '0 1 2'.
Correct Answer:
A
— 0 1 2
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Q. Which algorithm is guaranteed to find the shortest path in a graph with negative weight edges?
A.
Dijkstra's algorithm
B.
A* algorithm
C.
Bellman-Ford algorithm
D.
Floyd-Warshall algorithm
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Solution
The Bellman-Ford algorithm is guaranteed to find the shortest path in graphs with negative weight edges, unlike Dijkstra's algorithm.
Correct Answer:
C
— Bellman-Ford algorithm
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Q. Which greedy algorithm is used to solve the activity selection problem?
A.
Dijkstra's algorithm
B.
Kruskal's algorithm
C.
Interval scheduling maximization
D.
Prim's algorithm
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Solution
The activity selection problem is solved using the interval scheduling maximization greedy algorithm.
Correct Answer:
C
— Interval scheduling maximization
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Q. Which of the following data structures is commonly used to implement BFS?
A.
Stack
B.
Queue
C.
Linked List
D.
Array
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Solution
BFS uses a Queue data structure to keep track of the nodes that need to be explored next.
Correct Answer:
B
— Queue
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Q. Which of the following is a base case in a recursive function?
A.
The case that leads to infinite recursion
B.
The case that stops the recursion
C.
The case that calls the function again
D.
The case that doubles the input size
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Solution
A base case is the condition under which the recursion stops, preventing infinite recursion.
Correct Answer:
B
— The case that stops the recursion
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Q. Which of the following is a characteristic of dynamic programming?
A.
It always uses recursion
B.
It requires a greedy approach
C.
It stores results of subproblems
D.
It is only applicable to optimization problems
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Solution
Dynamic programming is characterized by storing the results of subproblems to avoid redundant calculations, which improves efficiency.
Correct Answer:
C
— It stores results of subproblems
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Q. Which of the following is a common application of a queue?
A.
Function call management
B.
Undo functionality in text editors
C.
Breadth-first search in graphs
D.
Expression evaluation
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Solution
Queues are commonly used in breadth-first search algorithms to manage the nodes to be explored.
Correct Answer:
C
— Breadth-first search in graphs
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Q. Which of the following is a common application of greedy algorithms?
A.
Sorting data
B.
Finding the shortest path
C.
Job scheduling
D.
All of the above
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Solution
Job scheduling is a common application of greedy algorithms, particularly in maximizing resource utilization.
Correct Answer:
C
— Job scheduling
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Q. Which of the following is a valid variable declaration in C?
A.
int 1number;
B.
float number1;
C.
char number#;
D.
double number@;
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Solution
The valid variable declaration in C is float number1; as variable names cannot start with a digit or contain special characters.
Correct Answer:
B
— float number1;
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Q. Which of the following is an example of a problem that can be solved using divide and conquer?
A.
Binary search
B.
Fibonacci sequence
C.
Linear search
D.
Bubble sort
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Solution
Binary search is an example of a divide and conquer algorithm, as it divides the search space in half.
Correct Answer:
A
— Binary search
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Q. Which of the following is an example of a problem that can be solved using dynamic programming?
A.
Finding the maximum sum of a contiguous subarray
B.
Finding the maximum element in an array
C.
Sorting an array of integers
D.
Searching for an element in an unsorted array
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Solution
Finding the maximum sum of a contiguous subarray can be solved using dynamic programming, specifically with Kadane's algorithm.
Correct Answer:
A
— Finding the maximum sum of a contiguous subarray
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Q. Which of the following is not a characteristic of a linked list?
A.
Dynamic size
B.
Random access
C.
Efficient insertions/deletions
D.
Non-contiguous memory allocation
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Solution
Linked lists do not support random access; elements must be accessed sequentially.
Correct Answer:
B
— Random access
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Q. Which of the following is NOT a characteristic of greedy algorithms?
A.
They make decisions based on current information
B.
They do not reconsider previous decisions
C.
They guarantee an optimal solution for all problems
D.
They are often faster than other algorithms
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Solution
Greedy algorithms do not guarantee an optimal solution for all problems; they work well for specific types of problems.
Correct Answer:
C
— They guarantee an optimal solution for all problems
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Q. Which of the following is NOT a step in the dynamic programming approach?
A.
Characterizing the structure of an optimal solution
B.
Recursively solving the problem
C.
Storing the results of subproblems
D.
Constructing a solution from optimal subsolutions
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Solution
While recursion can be used in dynamic programming, it is not a necessary step; dynamic programming can also be implemented iteratively.
Correct Answer:
B
— Recursively solving the problem
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Q. Which of the following is not a valid pointer declaration in C?
A.
int *ptr;
B.
float ptr;
C.
char *ptr;
D.
double *ptr;
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Solution
The declaration float ptr; is not a pointer declaration; it is a regular float variable.
Correct Answer:
B
— float ptr;
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Q. Which of the following is NOT a valid tree traversal method?
A.
In-order
B.
Pre-order
C.
Post-order
D.
Side-order
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Solution
Side-order is not a recognized tree traversal method.
Correct Answer:
D
— Side-order
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Q. Which of the following is true about pointers?
A.
Pointers can only point to integers
B.
Pointers can point to any data type
C.
Pointers cannot be reassigned
D.
Pointers are always initialized to zero
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Solution
Pointers can point to any data type, allowing for flexible memory management.
Correct Answer:
B
— Pointers can point to any data type
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Q. Which of the following is true about recursive algorithms?
A.
They always run faster than iterative algorithms
B.
They can be less memory efficient due to call stack
C.
They cannot be used for sorting
D.
They are always easier to understand
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Solution
Recursive algorithms can be less memory efficient due to the overhead of maintaining the call stack.
Correct Answer:
B
— They can be less memory efficient due to call stack
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Q. Which of the following operations can be performed in constant time on a queue?
A.
Enqueue
B.
Dequeue
C.
Peek
D.
All of the above
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Solution
All of the operations (Enqueue, Dequeue, and Peek) can be performed in constant time, O(1), in a properly implemented queue.
Correct Answer:
D
— All of the above
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Q. Which of the following operations is NOT typically associated with a queue?
A.
Enqueue
B.
Dequeue
C.
Peek
D.
Push
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Solution
The 'Push' operation is associated with stacks, while queues use 'Enqueue' to add and 'Dequeue' to remove elements.
Correct Answer:
D
— Push
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Q. Which of the following problems can be solved using a greedy algorithm?
A.
Knapsack problem
B.
Minimum spanning tree
C.
Shortest path in a graph
D.
All of the above
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Solution
The minimum spanning tree can be solved using a greedy algorithm, while the knapsack problem is not always solvable by greedy methods.
Correct Answer:
B
— Minimum spanning tree
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