Time Complexity Analysis PDF
Preview Time Complexity Analysis
This book “Time Complexity Analysis” introduces you to the basics of Time Complexity notations, meaning of the Complexity values and How to analyze various Algorithmic problems. This book includes Time and Space Complexity cheat sheets at the end as a bonus resource.
We have tackled several significant problems and demonstrated the approach to analyze them and arrived at the Time and Space Complexity of the problems and Algorithms.
This is a MUST-READ book for all Computer Science students and Programmers. Do not miss this opportunity.
You will get a better idea to judge which approach will work better and will be able to make better judgements in your development work.
See the “Table of content” to get the list of exciting topics you will learn about.
Some of the key points you will understand
Random Access Memory does not take O(1) time. It is complicated and in general, has a Time Complexity of O(√N).
Multiplication takes O(N^2) time, but the most optimal Algorithm (developed in 2019) takes O(N logN) time which is believed to be the theoretical limit.
As per Time Complexity, finding the largest element and the i-th largest element takes the same order of time.
It is recommended that you go through this book twice. First time, you may skip the minute details that you may not understand at first go and get the overview.
In the second reading, you will get all the ideas, and this will strengthen your insights.
In 1950s, Computing was not a Science.
It was a collective effort by several Computer Scientists such as Robert Tarjan and Philippe Flajolet who analyzed several computational problems to demonstrate that Computation Problems are equally complicated as Physics and Mathematics Problems. The ideas captured in this book include some of these analyses which glorified Computer Science and made it a Scientific field.
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