- Data Structures & Algorithms
- DSA - Home
- DSA - Overview
- DSA - Environment Setup
- DSA - Algorithms Basics
- DSA - Asymptotic Analysis
- Data Structures
- DSA - Data Structure Basics
- DSA - Data Structures and Types
- DSA - Array Data Structure
- Linked Lists
- DSA - Linked List Data Structure
- DSA - Doubly Linked List Data Structure
- DSA - Circular Linked List Data Structure
- Stack & Queue
- DSA - Stack Data Structure
- DSA - Expression Parsing
- DSA - Queue Data Structure
- Searching Algorithms
- DSA - Searching Algorithms
- DSA - Linear Search Algorithm
- DSA - Binary Search Algorithm
- DSA - Interpolation Search
- DSA - Jump Search Algorithm
- DSA - Exponential Search
- DSA - Fibonacci Search
- DSA - Sublist Search
- DSA - Hash Table
- Sorting Algorithms
- DSA - Sorting Algorithms
- DSA - Bubble Sort Algorithm
- DSA - Insertion Sort Algorithm
- DSA - Selection Sort Algorithm
- DSA - Merge Sort Algorithm
- DSA - Shell Sort Algorithm
- DSA - Heap Sort
- DSA - Bucket Sort Algorithm
- DSA - Counting Sort Algorithm
- DSA - Radix Sort Algorithm
- DSA - Quick Sort Algorithm
- Graph Data Structure
- DSA - Graph Data Structure
- DSA - Depth First Traversal
- DSA - Breadth First Traversal
- DSA - Spanning Tree
- Tree Data Structure
- DSA - Tree Data Structure
- DSA - Tree Traversal
- DSA - Binary Search Tree
- DSA - AVL Tree
- DSA - Red Black Trees
- DSA - B Trees
- DSA - B+ Trees
- DSA - Splay Trees
- DSA - Tries
- DSA - Heap Data Structure
- Recursion
- DSA - Recursion Algorithms
- DSA - Tower of Hanoi Using Recursion
- DSA - Fibonacci Series Using Recursion
- Divide and Conquer
- DSA - Divide and Conquer
- DSA - Max-Min Problem
- DSA - Strassen's Matrix Multiplication
- DSA - Karatsuba Algorithm
- Greedy Algorithms
- DSA - Greedy Algorithms
- DSA - Travelling Salesman Problem (Greedy Approach)
- DSA - Prim's Minimal Spanning Tree
- DSA - Kruskal's Minimal Spanning Tree
- DSA - Dijkstra's Shortest Path Algorithm
- DSA - Map Colouring Algorithm
- DSA - Fractional Knapsack Problem
- DSA - Job Sequencing with Deadline
- DSA - Optimal Merge Pattern Algorithm
- Dynamic Programming
- DSA - Dynamic Programming
- DSA - Matrix Chain Multiplication
- DSA - Floyd Warshall Algorithm
- DSA - 0-1 Knapsack Problem
- DSA - Longest Common Subsequence Algorithm
- DSA - Travelling Salesman Problem (Dynamic Approach)
- Approximation Algorithms
- DSA - Approximation Algorithms
- DSA - Vertex Cover Algorithm
- DSA - Set Cover Problem
- DSA - Travelling Salesman Problem (Approximation Approach)
- Randomized Algorithms
- DSA - Randomized Algorithms
- DSA - Randomized Quick Sort Algorithm
- DSA - Karger’s Minimum Cut Algorithm
- DSA - Fisher-Yates Shuffle Algorithm
- DSA Useful Resources
- DSA - Questions and Answers
- DSA - Quick Guide
- DSA - Useful Resources
- DSA - Discussion
Data Structures Algorithms Online Quiz
Following quiz provides Multiple Choice Questions (MCQs) related to Data Structures Algorithms. You will have to read all the given answers and click over the correct answer. If you are not sure about the answer then you can check the answer using Show Answer button. You can use Next Quiz button to check new set of questions in the quiz.
Q 1 - Which of the following usees FIFO method
Answer : A
Explanation
Queue maintains two pointers − front and rear. In queue data structure, the item inserted first will always be removed first, hence FIFO!
Q 2 - Maximum number of nodes in a binary tree with height k, where root is height 0, is
Answer : B
Explanation
If the root node is at height 0, then a binary tree can have at max 2k+1 − 1 nodes.
For example: a binary tree of height 1, can have maximum 21+1 − 1 = 3 nodes.
r --------- 0 / \ L R --------- 1
Q 3 - Quick sort algorithm is an example of
Answer : D
Explanation
Quick sort divides the list using pivot and then sorts in recursive manner. It uses divide and conquer approach.
Q 4 - Maximum degree of any vertex in a simple graph of vertices n is
Answer : D
Explanation
In a simple graph, a vertex can have edge to maximum n - 1 vertices.
Q 5 - What about recursion is true in comparison with iteration?
A - very expensive in terms of memory.
C - every recursive program can be written with iteration too.
Answer : D
Explanation
Recursion is just an other way to write the same program code. But calling a function again and again makes it expensive in terms of memory, CPU cycles and delivers less performance.
Q 6 - Which of the below given sorting techniques has highest best-case runtime complexity −
Answer : B
Explanation
Selection sort best case time complexity is Ο(n2)
Q 7 - The Θ notation in asymptotic evaluation represents −
Answer : A
Explanation
Θ represents average case. Ο represents worst case and Ω represents base case.
Q 8 - In the deletion operation of max heap, the root is replaced by
A - next available value in the left sub-tree.
B - next available value in the right sub-tree.
Answer : D
Explanation
Regardless of being min heap or max heap, root is always replaced by last element of the last level.
Q 9 - The following sorting algorithms maintain two sub-lists, one sorted and one to be sorted −
Answer : D
Explanation
Both selection sort and insertion sort maintains two sublists and then checks unsorted list for next sorted element.
Q 10 - Which of the following algorithm does not divide the list −
Answer : A
Explanation
Linear search, seaches the desired element in the target list in a sequential manner, without breaking it in any way.
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