- 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
- DSA - Skip List 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
- DSA - Circular Queue Data Structure
- DSA - Priority Queue Data Structure
- DSA - Deque 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 Algorithm
- DSA - Bucket Sort Algorithm
- DSA - Counting Sort Algorithm
- DSA - Radix Sort Algorithm
- DSA - Quick Sort Algorithm
- Matrices Data Structure
- DSA - Matrices Data Structure
- DSA - Lup Decomposition In Matrices
- DSA - Lu Decomposition In Matrices
- Graph Data Structure
- DSA - Graph Data Structure
- DSA - Depth First Traversal
- DSA - Breadth First Traversal
- DSA - Spanning Tree
- DSA - Topological Sorting
- DSA - Strongly Connected Components
- DSA - Biconnected Components
- DSA - Augmenting Path
- DSA - Network Flow Problems
- DSA - Flow Networks In Data Structures
- DSA - Edmonds Blossom Algorithm
- DSA - Maxflow Mincut Theorem
- 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 - Range Queries
- DSA - Segment Trees
- DSA - Fenwick Tree
- DSA - Fusion Tree
- DSA - Hashed Array Tree
- DSA - K-Ary Tree
- DSA - Kd Trees
- DSA - Priority Search Tree 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 Sub-sequence Algorithm
- DSA - Travelling Salesman Problem (Dynamic Approach)
- Hashing
- DSA - Hashing Data Structure
- DSA - Collision In Hashing
- Disjoint Set
- DSA - Disjoint Set
- DSA - Path Compression And Union By Rank
- Heap
- DSA - Heap Data Structure
- DSA - Binary Heap
- DSA - Binomial Heap
- DSA - Fibonacci Heap
- Tries Data Structure
- DSA - Tries
- DSA - Standard Tries
- DSA - Compressed Tries
- DSA - Suffix Tries
- Treaps
- DSA - Treaps Data Structure
- Bit Mask
- DSA - Bit Mask In Data Structures
- Bloom Filter
- DSA - Bloom Filter Data Structure
- 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
- Miscellaneous
- DSA - Infix to Postfix
- DSA - Bellmon Ford Shortest Path
- DSA - Maximum Bipartite Matching
- DSA Useful Resources
- DSA - Questions and Answers
- DSA - Selection Sort Interview Questions
- DSA - Merge Sort Interview Questions
- DSA - Insertion Sort Interview Questions
- DSA - Heap Sort Interview Questions
- DSA - Bubble Sort Interview Questions
- DSA - Bucket Sort Interview Questions
- DSA - Radix Sort Interview Questions
- DSA - Cycle Sort Interview Questions
- 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 - What is the worst case time complexity of linear search algorithm?
Answer : D
Explanation
Linear search scans sequentially to find the target value. The best case is Ο(1) and average and worst case is Ο(n). Worst case is when data is not in the list, and it has to scan all n elements.
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 - Minimum number of moves required to solve a Tower of Hanoi puzzle is
Answer : C
Explanation
Minimum number of moves required to solve a Tower of Hanoi puzzle is 2n - 1. Where n is the number of disks. If the number of disks is 3, then minimum number of moves required are 23 - 1 = 7
Q 4 - What could be the worst case height of an AVL tree?
Answer : C
Explanation
Worst case height of an AVL tree is 1.44 log n
Q 5 - Apriory algorithm analysis does not include −
Answer : C
Explanation
Algorithms are independent of programming languages, hence, program complexity is not a part of algorithm analysis.
Q 6 - What will be the running-time of Dijkstra's single source shortest path algorithm, if the graph G(V,E) is stored in form of adjacency list and binary heap is used −
Answer : C
Explanation
The runing time will be Ο(|E|+|V| log |V|) when we use adjacency list and binary heap.
Answer : B
Explanation
Linked lists has search complexity of Ο(n).
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 - A balance factor in AVL tree is used to check
B - if all child nodes are at same level.
Answer : D
Explanation
The balance factor (BalanceFactor = height(left-sutree) height(right-sutree)) is used to check if the tree is balanced or unbalanced.
Q 10 - Apriori analysis of an algorithm assumes that −
A - the algorithm has been tested before in real environment.
B - all other factors like CPU speed are constant and have no effect on implementation.
Answer : B
Explanation
Efficiency of algorithm is measured by assuming that all other factors e.g. processor speed, are constant and have no effect on implementation.