Introduction to Algorithms

Additional Introduction to Algorithms Information

In its new edition, Introduction to Algorithms continues to provide a comprehensive introduction to the modern study of algorithms. The revision has been updated to reflect changes in the years since the book's original publication. New chapters on the role of algorithms in computing and on probabilistic analysis and randomized algorithms have been included. Sections throughout the book have been rewritten for increased clarity, and material has been added wherever a fuller explanation has seemed useful or new information warrants expanded coverage.

As in the classic first edition, this new edition of Introduction to Algorithms presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers. Further, the algorithms are presented in pseudocode to make the book easily accessible to students from all programming language backgrounds.

Each chapter presents an algorithm, a design technique, an application area, or a related topic. The chapters are not dependent on one another, so the instructor can organize his or her use of the book in the way that best suits the course's needs. Additionally, the new edition offers a 25% increase over the first edition in the number of problems, giving the book 155 problems and over 900 exercises that reinforce the concepts the students are learning.

What Customers Say About Introduction to Algorithms:

Given this book's steep mathematical requirements (discrete math, graph theory, combinatorics, and matrices), it's lack of explanations / demonstrations, and, from my experience, it's use in computer science courses without a steep math pre-requisite this book is inappropriately titled and difficult to use. Yes, mathematics are vital to the understanding and practice of any science. This book demonstrates the growing divide between mathematics and computer science. If you already know the math and just want to apply it, then this book will be of tremendous use to you. Yes, computer science is closer to physics than biology or chemistry when it comes to math usage. However, this does not make every aspiring computer scientist a mathematician. If you don't know the math and think you'll learn what you need as you go along, then you'd better have a mathematician handy to help you out with that, because this book will leave you hanging.if you attend MIT or another school with a HEAVY math emphasis, then this book will serve you well. If you've had nothing but Calculus, then this book may leave you enraged and confused with a strong preference for heuristics.As it stands I hope the third edition is much improved, for the sake of students everywhere, and I wonder why my class (fall 2009) did not use it instead.

It does not describe any strategy to begin in a useful manner. This book is readable. It gives few examples with limited explanation. I gave it two stars because of how I feel: the alt text reads "I don't like it."I tried with significant effort to read and understand this book. It does not give an in depth explanation of analysis, in my case, of recurrence. It does not provide any sample problem/solution breakdowns. All of which I feel would benefit my learning methods greatly.If this book had an introduction to "Introduction to Algorithms".

This is the best algorithms book ever. It covers the whole gamut of topics from sorting to graphs to NP-complete problems. It's so good that if you study computer science, you'd want this book on your bookshelf for reference even if no course explicitly requires it. Highly recommended.

My son is a Computer Engineer student, he found this book very useful and valuable support in this subject.

Great wide area covering algorithms book. It's covering many areas , and gives good starting ( sometimes not just start ) point for investigation of some concrete problem. It's not dependent on some concrete programming language , and examples are written in pseudocode.