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 6 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

Q51.

In simple terms, we can say that an algorithm is a step-by-step procedure for performing some task in a finite amount of time. State if the statement is true or false.

False

True

Maybe

None of the above

Discuss

Answer: (b).True

Q52.

Each operation must have a definite meaning and it must be perfectly clear. All steps of an algorithm need to be precisely defined. The actions to be executed in each case should be _____________.

Rigorously specified

Clearly specified

Both (a) and (b)

None of the above

Discuss

Answer: (c).Both (a) and (b)

Q53.

In general, a problem may be defined as a state of thing that is not in the___________.

Wrong order

Opposite order

Right order

None of the above

Discuss

Answer: (c).Right order

Q54.

An algorithm that requires ................... operations to complete its task on n data elements is said to have a linear runtime.

n^3 + 9

3n^2 + 3n + 2

2n + 1

Discuss

Answer: (c).2n + 1

Q55.

The complexity of adding two matrices of order m*n is

m + n

max(m, n)

min(m, n)

Discuss

Answer: (b).mn

Q56.

lg (n!) = .................

O(n)

O(lg n)

O(n^2)

O(n lg n)

Discuss

Answer: (d).O(n lg n)

Q57.

Which of the following uses memorization?

Greedy approach

Divide and conquer approach

Dynamic programming approach

None of the above

Discuss

Answer: (c).Dynamic programming approach

Q58.

An algorithm is made up of 2 modules M1&M2.; If order of M1 is f(n) & M2 is g(n) then the order of algorithm is?

f(n) + g(n)

f(n) X g(n)

max (f(n),g(n))

min (f(n),g(n))

Discuss

Answer: (d).min (f(n),g(n))

Q59.

An array of n numbers is given, where n is an even number. The maximum as well as the minimum of these n numbers needs to be determined. Which of the following is TRUE about the number of comparisons needed?

At most 1.5n-2 comparisons are needed.

At least nlog2n comparisons are needed.

At least 2n-c comparisons, for some constant c, are needed.

None of the above

Discuss

Answer: (a).At most 1.5n-2 comparisons are needed.

Q60.

The running time of an algorithm T(n),where 'n' is the input size, of a recursive algorithm is given as follows.is given by T(n) =c + T(n - 1), if n > 1 d, if n ≤ 1 The order of this algorithm is

n+1

n-1

n*1

Discuss

Answer: (a).n

Page 6 of 10

Welcome to the Algorithm Complexity MCQs Page

Algorithm Complexity MCQs | Page 6 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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