Welcome to the Algorithm Complexity MCQs Page

Dive deep into the fascinating world of Algorithm Complexity with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Algorithm Complexity, a crucial aspect of Data Structures and Algorithms. In this section, you will encounter a diverse range of MCQs that cover various aspects of Algorithm Complexity, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Data Structures and Algorithms.

Check out the MCQs below to embark on an enriching journey through Algorithm Complexity. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Data Structures and Algorithms.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Algorithm Complexity. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Algorithm Complexity MCQs | Page 2 of 10

Explore more Topics under Data Structures and Algorithms

01

Data Structures Basics

02

Data Types and Abstraction

03

Arrays and Pointers

04

Linked Lists

05

Stacks and Queues

06

Recursion

07

Trees

08

Graphs

09

String Operations

10

Sorting and Searching

11

Object Oriented Programming

12

Dynamic Programming

Q11.

Travelling salesman problem is an example of

Dynamic Algorithm

Greedy Algorithm

Recursive Approach

Divide & Conquer

Discuss

Answer: (b).Greedy Algorithm

Q12.

Project scheduling is an example of

greedy programming

dynamic programming

divide and conquer

none of the above.

Discuss

Answer: (b).dynamic programming

Q13.

Which of the following is an example of dynamic programming approach?

Fibonacci Series

Tower of Hanoi

Dijkstra Shortest Path

All of the above

Discuss

Answer: (d).All of the above

Q14.

Which of the following uses memoization?

Greedy approach

Divide and conquer approach

Dynamic programming approach

None of the above

Discuss

Answer: (c).Dynamic programming approach

Q15.

Which of the following asymptotic notation is the worst among all?

Ο(n+9378)

Ο(n3)

nΟ(1)

2Ο(n)

Discuss

Answer: (b).Ο(n3)

Q16.

Minimum number of moves required to solve a Tower of Hanoi puzzle is

2n2

2n-1

2n - 1

Discuss

Answer: (d).2n - 1

Q17.

Program with highest run-time complexity is

Tower of Hanoi

Fibonacci Series

Prime Number Series

None of the above

Discuss

Answer: (a).Tower of Hanoi

Q18.

The time complexity of quick sort is …………..

O(n)

O(n2)

O(n log n)

O(log n)

Discuss

Answer: (c).O(n log n)

Q19.

Two main measures for the efficiency of an algorithm are

Processor and memory

Complexity and capacity

Time and space

Data and space

Discuss

Answer: (c).Time and space

Q20.

The time factor when determining the efficiency of algorithm is measured by

Counting microseconds

Counting the number of key operations

Counting the number of statements

Counting the kilobytes of algorithm

Discuss

Answer: (b).Counting the number of key operations

Page 2 of 10

Welcome to the Algorithm Complexity MCQs Page

Algorithm Complexity MCQs | Page 2 of 10

Explore more Topics under Data Structures and Algorithms

Data Structures Basics

Data Types and Abstraction

Arrays and Pointers

Linked Lists

Stacks and Queues

Recursion

Trees

Graphs

String Operations

Sorting and Searching

Object Oriented Programming

Dynamic Programming

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