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An Introduction to the Analysis of Algorithms Hardcover – 18 Jan 2013

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About the Author

Robert Sedgewick is the William O. Baker Professor of Computer Science at Princeton University, where was founding chair of the computer science department and has been a member of the faculty since 1985. He is a Director of Adobe Systems and has served on the research staffs at Xerox PARC, IDA, and INRIA. He is the coauthor of the landmark introductory book, Algorithms, Fourth Edition. Professor Sedgewick earned his Ph.D from Stanford University under Donald E. Knuth.


The late Philippe Flajolet was a Senior Research Director at INRIA, Rocquencourt, where he created and led the ALGO research group. He is celebrated for having opened new lines of research in the analysis of algorithms; having systematized and developed powerful new methods in the field of analytic combinatorics; having solved numerous difficult, open problems; and having lectured on the analysis of algorithms all over the world. Dr. Flajolet was a member of the French Academy of Sciences.

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Most Helpful Customer Reviews on (beta) 4 reviews
26 of 27 people found the following review helpful
A valuable read 4 Mar. 2013
By Roc - Published on
Format: Hardcover
This is a highly digestible math book and the focus is on a formal approach of accurate analysis (not just worst case or average case) for most algorithms. It is not a substitute of the CLRS or other popular textbooks, it is a somewhat different approach. The text tells you what you need to worry about when analyzing algorithmic topics, and explains the "how"s very clearly and nicely paced. The effect is that while reading, I never have the dread that I am not able to finish a typical thousand-page theory book. It prepares you for the author's Analytic Combinatorics and Knuth's TAOCP, but I find it equally useful just to better understand algorithms overall.
7 of 7 people found the following review helpful
Uncommonly good 10 Jun. 2014
By Customer - Published on
Format: Hardcover Verified Purchase
I am a first year graduate student in mathematics, so keep that in mind if you're trying to generalize my review. I use nearly all the math discussed in the text for analytic number theory (I rarely program), but this book gives an especially nice treatment of the combinatorial mathematics. I really get excited every time I have to open this book.

I typically learn best from books, so I have a good sense for what a book should feature for me to learn the material as quickly and effectively as possible. It's really a drag when something as superfluous as style or a purist aesthetic makes reading sluggish or just impossible to learn from. I want a book to have many problems (ranging between medium to very hard/open problems), solutions in the back, examples to make the more difficult concepts clear, both historical and modern motivations for the material, and clean, linear descriptions. This book hits all of these except the "solutions in the back" part. Despite this one "flaw", however, this book has other great features that compensate. For example, the typesetting is fresh and makes the text more engaging. Also, there are very beautiful graphs and great reference tables. It is really a wonderful book -- the authors clearly were purposeful in the design of this text.
1 of 1 people found the following review helpful
Five Stars 17 Nov. 2014
By J. Lohse - Published on
Format: Kindle Edition Verified Purchase
You can't beat this book for studying algorithms.
13 of 20 people found the following review helpful
Review for Kindle Edition ONLY 13 Sept. 2013
By Amazon Customer - Published on
Format: Kindle Edition
The Kindle edition (at least judging by the free sample) has some formatting issues that render it not so usable. Of all things, in monospaced code samples the plus sign and minus signs ("+", "++", "-", "--") are not rendered on Kindle for PC (1.10.6).

Other than that, the formatting appears to be better than in many Kindle math/CS textbooks, but mis-rendered code samples make this a non-purchase for me.
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