Top 45+ DSA MCQ.Questions with Answers {Updated}

Top 45+ DSA MCQ.Questions with Answers {Updated}

24 Jun 2024
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Do you want to revise your data structures concepts quickly? I must tell you MCQs are the best way to revise any topic in less time. We know that data structures are vast and a very important topic. No matter whether you are going for a Java developer interview, a .NET developer interview, or an Angular developer interview; questions from data structures will be asked.

We are here with the Data Structures MCQ Question and Answers in this DSA tutorial to speed up your interview preparation. If your interview is going to start in 10-15 minutes, you can easily go through these MCQs on your mobile.

1. What is a data structure?

  1. Programming language
  2. Database Design
  3. Storage and Data Organization Technique
  4. collection of algorithms

Ans. Data Structure is storing and organizing data in the computer memory. It is the branch of computer science that deals with arranging large datasets in such a manner that they can be accessed and modified as per the requirements.

Read More: What are Data Structures - Types of Data Structures (Complete Guide)

2. The insertion operation in the stack is known as:

  1. Add
  2. Push
  3. Insert
  4. Interpolate

Ans. Pushing means inserting an element at the top of the stack.

3. How can array elements be accessed?

  1. randomly
  2. sequentially
  3. exponentially
  4. logarithmically

Ans. The array elements are stored at contagious memory locations that can be randomly accessed with their index number.

4. Which of the following cases does not exist in complexity theory?

  1. Best case
  2. Worst case
  3. Average case
  4. Empty Case

5. Which data structure is based on the First In Last Out (FILO) principle?

  1. Queue
  2. Stack
  3. Tree
  4. Graph

Ans. The last inserted element is available first and is the first one to be deleted. Hence, it is known as Last In, First Out LIFO, or First In, Last Out FILO.

6. The prefix form of ((a/b)+c)-(d+(e*f)) is?

  1. - + / a b c + d * e f
  2. + - / a b c + d * e f
  3. - + a / b c d + * e f
  4. - / a b + c + d * e f

Ans. Let's see the step-by-step conversion of the infix expression, "((a/b)+c)-(d+(e*f))" into prefix:

  1. Reverse the Infix Expression: ))f*e(+d(-)c+)b/a((
  2. Interchange '(' with ')' and vice versa: ((f*e)+d)-(c+(b/a))
  3. Apply postfix
    ExpressionStackOperationOutput
    ((f*e)+d)-(c+(b/a))(Push
    (f*e)+d)-(c+(b/a))((Push
    f*e)+d)-(c+(b/a))(( f
    *e)+d)-(c+(b/a))((*Pushf
    e)+d)-(c+(b/a))((*-fe
    )+d)-(c+(b/a))((Popfe*
    +d)-(c+(b/a))((+Pushfe*
    d)-(c+(b/a))((+ fe*d
    )-(c+(b/a))((Popfe*d+
    -(c+(b/a))((-Pushfe*d+
    (c+(b/a))((-(Pushfe*d+
    c+(b/a))((-( fe*d+c
    +(b/a))((-(+Pushfe*d+c
    (b/a))((-(+(Pushfe*d+c
    b/a))((-(+( fe*d+cb
    /a))((-(+( /Pushfe*d+cb
    a))((-(+( / fe*d+cba
    ))((-(+(Popfe*d+cba/
    )((-(Popfe*d+cba/+
    Popfe*d+cba/+-
  4. Reverse the postfix expression to get the prefix.
Read More: Implementing Stack in Data Structures

7. Which of the following applications uses a circular linked list?

  1. Recursive function calls
  2. Undo operation in a text editor
  3. Implement Hash Tables
  4. Allocating CPU to resources

Ans. Round Robin is employed to allocate CPU time to resources using the circular linked list data structure.

8. What's the worst-case scenario in a linear search algorithm?

  1. The element is somewhere in the middle of the array
  2. The element is not present in the array
  3. The element is the last in the array
  4. Either the element is the last in the array or is not there

9. Which of the following is not a balanced binary tree?

  1. Splay tree
  2. B-tree
  3. AVL tree
  4. Red-black tree

Ans. B-Tree is a self-balancing tree where a node can have more than two children

Read More: B Tree: An Efficient Data Structure

10. Which of the following is not a type of queue?

  1. Priority queue
  2. Circular queue
  3. Single-ended queue
  4. Ordinary queue

Ans. A queue is an ordered list in which insertion is done at one end and deletion at another.

11. The complexity of the average case of an algorithm is

  1. more complicated to analyze than the worst-case
  2. Much simpler to analyze than the worst-case
  3. Sometimes more complicated and some other times simpler than the worst-case
  4. None of the above

12. The time complexity of the dequeue operation in a queue is

  1. O(1)
  2. O(n)
  3. O(long)
  4. O(n logn)

Ans. The dequeue operation involves removing the front element and updating the front pointer.

Read More: Complexity Analysis of Data Structures and Algorithms

13. How will you increment the rear end in a circular queue?

  1. rear =rear+1
  2. (rear+1) % max
  3. (rear % max) + 1
  4. None of the above

Ans. The rear value will be from 0 to max-1. max is the total size of the circular queue. rear + 1 moves the rear pointer to the next position. (rear+1) % max will point to the first position in the queue maintaining the circular nature.

14. What would be the time complexity to find an element in the linked list?

  1. O(1)
  2. O(n)
  3. O(n^2)
  4. O(n^4)

Ans. If the element is at the end of the linked list, we have to traverse through all the linked list elements.

15. Which sorting algorithm can sort a random linked list with minimum time complexity?

  1. Insertion Sort
  2. Quick Sort
  3. Heap Sort
  4. Merge Sort

Ans. The worst-case time complexity of Merge Sort is O(n Logn). Here, n is the number of elements in the linked list.

16. A one-dimensional array containing one-dimensional arrays is called

  1. Two-dimensional array
  2. Multi-casting array
  3. Multi-dimensional array
  4. Three-dimensional array

17. The data structure used to check whether an expression contains a balanced parenthesis is?

  1. Queue
  2. Stack
  3. Tree
  4. Array

Ans. Stack works according to the LIFO principle. Open parenthesis are pushed into the stack, and closed parenthesis pop out elements until the top element of the stack is its corresponding open parenthesis. If the stack is empty, the parenthesis are balanced.

18. Which algorithm stops the execution when it finds the solution otherwise start the problem from the top?

  1. Backtracking
  2. Divide and conquer
  3. Branch and Bound
  4. Dynamic programming

Ans. Backtracking solves the problem recursively and removes the solution if it does not satisfy the problem constraints. Whenever a solution fails we trace back to the failure point, build on the next solution, and continue this process till we find the solution or all possible solutions are looked after.

19. Which of the following data structures does the Tower of Hanoi algorithm use?

  1. Queue
  2. Linked List
  3. Heap
  4. Stack

20. A binary search algorithm cannot be applied to

  1. Sorted linked list
  2. Sorted linear array
  3. Sorted binary tree
  4. Pointer array

Ans. A binary search algorithm cannot be efficiently applied to a sorted linked list because it relies on random access to elements, which is a key feature of arrays but not linked lists.

21. What is an AVL tree?

  1. an unbalanced and height-balanced tree
  2. a balanced and height-balanced tree
  3. a tree with at most 3 children
  4. a tree with three children

Ans. AVL tree is a popular self-balancing binary search tree where the difference between the heights of left and right subtrees for any node does not exceed one. It automatically adjusts its structure to maintain the minimum possible height after any operation with the help of a balance factor for each node.

22. In a max-heap, the element with the greatest key is always in which node?

  1. Leaf node
  2. First node of left sub-tree
  3. root node
  4. First node of the right sub-tree

Ans. In a max-heap, all the nodes (including the root) are greater than their respective child nodes. The key of the root node is always the largest among all other nodes.

23. In a binary search tree, which traversals would print the numbers in ascending order?

  1. Level-order traversal
  2. Pre-order traversal
  3. Post-order traversal
  4. In-order traversal

Ans. In a binary search tree, each left subtree has values below the root and each right subtree has values above the root. An in-order traversal first visits the left child, then visits the node, and finally, the right child.

Read More: Binary Search Tree in Data Structures

24. When do you prefer Red-black trees over AVL trees?

  1. when there are more insertions or deletions
  2. when a large search operation is required
  3. when the tree must be balanced
  4. when log(nodes) time complexity is needed

Ans. Red-Black Trees require fewer rotations to maintain balance. On average, a Red-Black Tree requires at most 2 rotations for insertion and 3 rotations for deletion, while AVL Trees may require more rotations.

25. A graph with all vertices having equal degree is known as a

  1. Multi Graph
  2. Regular Graph
  3. Simple Graph
  4. Complete Graph

Ans. Regular Graph is an undirected graph where every vertex has the same number of edges or neighbors.

26. What is the term used when several elements compete for the same location in the hash table?

  1. Diffusion
  2. Replication
  3. Collision
  4. Duplication

Ans. A hash collision refers to a situation where two different inputs produce the same hash value or hash code when processed by a hash function.

27. A full binary tree can be generated using

  1. post-order and pre-order traversal
  2. pre-order traversal
  3. post-order traversal
  4. in-order traversal

Ans. A full binary tree is a tree in which every node has either 0 or 2 children.

28. B+ Trees are called balanced trees because

  1. the lengths of the paths from the root to all leaf nodes are equal.
  2. the lengths of the paths from the root to all leaf nodes differ from each other by at most 1
  3. the number of children of any two non-leaf sibling nodes differs by at most 1
  4. the number of records in any two leaf nodes differs by at most 1

29. An algorithm design method is used when the solution to a problem can be viewed as the result of a sequence of decisions

  1. Dynamic programming
  2. Backtracking
  3. Branch and bound
  4. Greedy method

Ans. This algorithm uses the already found solution to avoid repetitive calculation of the same part of the problem. It divides the problem into smaller overlapping subproblems, solves them, and stores the intermediate results.

30. Which algorithm type is used in solving the 4 Queens problem?

  1. Greedy
  2. Dynamic
  3. Branch and Bound
  4. Backtracking

31. Given an undirected graph G with V vertices and E edges, what will be the sum of the degrees of all vertices?

  1. E
  2. 2E
  3. V + E
  4. 2V

Ans. The degree of a vertex in a graph is the number of edges connected to that vertex.

Read More: Graphs in Data Structures - Types of Graphs, Representation & Operations

32. The necessary condition to be checked before deletion from the queue is

  1. Overflow
  2. Underflow
  3. Rear value
  4. Front value

Ans. Before deletion, we need to check whether the queue is empty or not.

33. BFS is best compared to DFS in the case of

  1. The graph’s width is large
  2. The graph’s depth is large
  3. The graph consists of many nodes
  4. The graph is complex

Ans. BFS explores all nodes at the present "depth" level before moving on to nodes at the next depth level. This ensures that the first time BFS reaches a node, it has found the shortest path to that node (in terms of the number of edges).

Read More: Breadth First Search vs Depth First Search

34. One of the differences between a queue and a stack is:

  1. Queues require dynamic memory, but stacks do not.
  2. Stacks require dynamic memory, but queues do not.
  3. Queues use two ends of the structure; stacks use only one.
  4. Stacks use two ends of the structure, and queues use only one

Ans. The stack has only one end, the top, at which both insertion and deletion take place. A queue has two ends, rear and front, for insertion and deletion respectively.

35. Which array operations have a time complexity of O(1)?

  1. Searching any element
  2. Accessing any element
  3. Inserting an element
  4. deleting an element

Ans. Accessing an element in an array can be done through indexing. So, it takes very little time.

36. What is the number of edges in a graph's minimum spanning tree with N vertices and E edges?

  1. E - 1
  2. N - 1
  3. N + E - 1
  4. N + E - 2

Ans. The number of edges in a spanning tree is equal to the number of nodes or vertices minus one i.e. n-1.

37. What is the time complexity of the merge sort algorithm?

  1. O(n)
  2. O(n^2)
  3. O(log n)
  4. O(n log n)

38. A self-balancing binary search tree can be used to implement

  1. Priority queue
  2. Hash table
  3. Heap sort
  4. Priority queue and Heap sort

Ans. A self-balancing binary search tree can implement a priority queue by efficiently managing insertions, deletions, and minimum/maximum element retrieval in O(logn) time.

39. What would be the color of a newly created node while inserting a new element in a Red-black tree?

  1. Black, if the new node is not a root node
  2. Red, if the new node is not a root node
  3. Black, if the new node is a root node
  4. Both b and c

Ans. If the newly created node is a root node, then it will be Black; otherwise, it will be Red.

40. Which one of the following algorithms does not return the optimal solution?

  1. Dynamic Programming
  2. Backtracking
  3. Branch and Bound
  4. Greedy Method

Ans. Backtracking solves the problem recursively and removes the solution if it does not satisfy the constraints of a problem. Whenever a solution fails we trace back to the failure point, build on the next solution, and continue this process till we find the solution or all possible solutions are looked after.

41. In a priority queue, insertion and deletion takes place at

  1. front, rear end
  2. only at the rear end
  3. only at the front end
  4. any position

Ans. In a priority queue, insertion takes place at the appropriate position to maintain the heap property, and deletion takes place at the root or the corresponding node.

42. O(n) means computing time is

  1. Constant
  2. Quadratic
  3. Linear
  4. Cubic

Ans. O(n) means the computing time grows linearly with the input size n.

43. The total number of comparisons in a bubble sort is

  1. n(n-1)/2
  2. 2n
  3. n^2
  4. n^3

Ans. The bubble sort algorithm repeatedly compares the adjacent elements, from left to right, and swaps them if they are out-of-order.

44. Which of the following is not an application of binary search?

  1. To find the lower/upper bound in an ordered sequence
  2. Union of intervals
  3. Debugging
  4. To search in an unordered list

Ans. Binary Search is a searching algorithm that searches for an element's position in a sorted array only.

45. What makes selection sorting different from other sorting techniques?

  1. It requires no additional storage space
  2. It is scalable
  3. It works best for already-sorted inputs
  4. It is faster than any other sorting technique

Ans. Selection sort is an in-place comparison sort algorithm. In-place sorting algorithms rearrange the elements within the array that is to be sorted, without using any additional space or memory.

Read More: Selection Sort in Data Structures

46. A linearly ordered sequence of memory cells is known as

  1. node
  2. link
  3. variable
  4. null

47. Associative arrays can be implemented using

  1. B-tree
  2. A doubly linked list
  3. A single linked list
  4. A self-balancing binary search tree

Ans. Associative arrays can be implemented using self-balancing binary search trees like AVL trees or Red-Black trees.

48. What is the worst-case time complexity of binary search using recursion?

  1. O(log n)
  2. O(n)
  3. O(n^2)
  4. O(nlogn)

49. What is the advantage of a recursive approach over an iterative approach?

  1. Consumes less memory
  2. Less code and easy to implement
  3. Consumes more memory
  4. More code has to be written

50. What is the hash function used in the division method?

  1. h(k) = k/m
  2. h(k) = k mod m
  3. h(k) = m/k
  4. h(k) = m mod k

Ans. The hash function in Data Structures is a function that takes a key and returns an index into the hash table. After that, it returns the value stored at that index which is known as the hash value.

Also read:
Summary

The above question covers almost all the important questions related to various data structures. You need to go through it again and again to gain conceptual clarity. We will try to provide MCQs on important topics related to data structures in the future.

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