1.1 Introduction

Question 1

What is an algorithm?

Answer 1

An algorithm is finite set of steps for solving a specific problem

Question 2

What are the characteristics of an algorithm?

Answer 2

• Finiteness
• Definiteness
• Input/Output
• Generality
• Effectiveness (every step can be converted to a programming language)

Question 3

What are the categories of algorithms?

Answer 3

• Sequential
• Iterative
• Selective

Question 4

What is the time complexity of an algorithm?

Answer 4

This is how much time is required for an algorithm to complete its execution

Question 5

What is the space complexity of an algorithm?

Answer 5

This is how much memory is required for an algorithm to complete execution.

Question 6

What is asymptotic analysis?

Answer 6

This is the mathematical analysis of the time or space required for an algorithm’s completion

Question 8

What are asymptotic notiations?

Answer 8

The mathematical notations used for asymptotic analysis

Question 9

Differentiate between the best, worst, and average case time complexity of an algorithm.

Answer 9

Best Case: The minimum amount of time required for the algorithm to complete execution

Average case: The typical amount of time required by an algorithm to complete the execution

Worst Case: The maximum amount of time required by an algorithm to complete execution

Question 10

What are the different asymptotic notations and their uses?

Answer 10

Big Oh (O): This is the notation used to represent the upper bound or worst-case complexity of an algorithm.

Omega: This notation is used to represent the best-case scenario or lower-bound of an algorithm

Theta: This notation is used to represent both the upper and lower bounds of an algorithm