- 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 - In a min-heap:
A - parent nodes have values greater than or equal to their childs
B - parent nodes have values less than or equal to their childs
Answer : A
Explanation
In a min heap, parents always have lesser or equal values than that of their childs.
Answer : B
Explanation
In queue, data item inserted first, will be available first and data item inserted last will be available in the last. FIFO stands for First In First Out and is a correct answer.
Q 3 - Which of the following is an example of dynamic programming approach?
Answer : D
Explanation
All mentioned use dynamic programming approach. Before solving the in-hand sub-problem, dynamic algorithm will try to examine the results of previously solved sub-problems. The solutions of sub-problems are combined in order to achieve the best solution.
Q 4 - Which of the following algorithm is not stable?
Answer : B
Explanation
Among the given, only quick sort is not stable that is it may re-arrange the already sorted items.
Q 5 - Which of the following has search effeciency of Ο(1) −
Answer : C
Explanation
A simple hash table has the Ω(1) efficiency.
Q 6 - Quick sort running time depends on the selection of
Answer : B
Explanation
If the pivot element is balanced, quick sort running time will be less.
Answer : B
Explanation
Linked lists has search complexity of Ο(n).
Q 8 - In a min heap
A - minimum values are stored.
B - child nodes have less value than parent nodes.
Answer : C
Explanation
In a min heap, parent nodes store lesser values than child nodes. The minimum value of the entire heap is stored at root.
Q 9 - Access time of a binary search tree may go worse in terms of time complexity upto
Answer : C
Explanation
At maximum, BST may need to search all n values in the tree in order to access an element, hence, Ο(n).
Q 10 - Aposterior analysis are more accurate than apriori analysis because −
A - it contains the real data.
B - it assumes all other factors to be dynamic.
Answer : B
Explanation
In this analysis, actual statistics like running time and space required, are collected.
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