Rating: 
Summary: bad, dont buy it
Review: bad written buy "introduction to algorithms"
Rating:
Summary: Poorly written
Review: First and foremost, this book was written in a "convserational" style. Considering they're discussing rigorous math, this is completely unforgivable. Secondly, almost everything in this book is poorly specified. For example, their definition of theta (average run time) allows for a negative a negative cost to run an algorithm. Lastly, most of the math presented in this godforsaken mess is completely invalid. One of the most prominent examples lies in the author's insistance on taking a derivative in a plane wherein the naturals are mapped to the x axis and reals are mapped to the y axis. Combine this with nearly intractable problems, and you've got a rather nasty mess on your hands. I'd strongly encourage anyone to avoid this book at all costs.
Rating:
Summary: Not very good
Review: I didn't like the organization of the book. It starts with page after page of the mathematics used to analyze algorithms. This could be shortened considerably. Then an analysis of some multiplication algorithms which are poorly explained. Most explanations are long winded and the pseudocode isn't that great. The one section that is o.k. is on probabilistic algorithms, including prime number generation and a little cryptology. In general there are many better books of this kind (Sedgewick, Baase, Corman, Aho, etc.)so that one wonders why this book is even out there. Maybe the author feels that organizing the book based on algorithmic technique as opposed to algorithmic function will help the reader. Sometimes it's just annoying since things like sorting are spread all over the book depending on the techniques used for the sort. Choose another book for algorithms.
Rating: 
Summary: It's a very good book for Algorithmic Techniques
Review: I don't agree with the other reviews. This book is a serious one and it is a "smooth" version of "Algorithms: Theory and Practice" from the same authors, which has a 5 stars rate. The book don't teach how to program, but the main kind of techniques in algorithm design (Greedy, Divide and Conquer and Dynamic Programing techniques, and others like Backtracking, Probabilistic Algorithms, etc.). I teach a course of Algorithm Design with this book (having the Sedgewick and Cormen books like additional very good references) and I think that it is a very instructive course on algorithmics (but NOT in programming, of course).
Rating:
Summary: It's a very good book for Algorithmic Techniques
Review: I don't agree with the other reviews. This book is a serious one and it is a "smooth" version of "Algorithms: Theory and Practice" from the same authors, which has a 5 stars rate. The book don't teach how to program, but the main kind of techniques in algorithm design (Greedy, Divide and Conquer and Dynamic Programing techniques, and others like Backtracking, Probabilistic Algorithms, etc.). I teach a course of Algorithm Design with this book (having the Sedgewick and Cormen books like additional very good references) and I think that it is a very instructive course on algorithmics (but NOT in programming, of course).
Rating:
Summary: Obtuse, incomplete explanations
Review: I had the misfortune of enduring this book during a graduate level course in algorithm analysis. Bad writing and incomplete explanations make the book a bad choice to learn this complex topic. Most of the itricate and particularly tricky parts of various proofs are left as "exercise to the reader"! Why bother when there are so many better ones to choose from?
Rating:
Summary: Fundamentals of Algorithmics
Review: One of the few books organising algorithms around design techniques instead of application areas (see "Algorithms" from Sedgevick). Though both approachs have pros and cons, I've found the former most convenient for people learning to design algorithms. Many problems admit several solutions depending on the design tecnique involved. This fact is emphasized by the authors.The book is self-contained, plainly written, so that an undergraduate can read it after taking a prerequisite course on programming. It's also mathematically rigorous, while mantaining simplicity. This allows analysis of algorithms to be really "analytic" (no more guessing the solution to a recurrence relation). One main drawback (certainly usual) is the lack of excercise solutions.
Rating:
Summary: Fundamentals of Algorithmics
Review: One of the few books organising algorithms around design techniques instead of application areas (see "Algorithms" from Sedgevick). Though both approachs have pros and cons, I've found the former most convenient for people learning to design algorithms. Many problems admit several solutions depending on the design tecnique involved. This fact is emphasized by the authors. The book is self-contained, plainly written, so that an undergraduate can read it after taking a prerequisite course on programming. It's also mathematically rigorous, while mantaining simplicity. This allows analysis of algorithms to be really "analytic" (no more guessing the solution to a recurrence relation). One main drawback (certainly usual) is the lack of excercise solutions.
Rating: 
Summary: Too conversational
Review: The reason I dislike this book is that it is written in a conversational style, which is very hard to follow. Being a beginner at this, it would be much more helpful if things were separated and clearly emphasized step by step. This book makes it difficult because all proofs are written into a big block of a paragraph. I normally have taken an hour or so to decode a paragraph so that I can say "Oh! That's what he meant." The content is good- layout is bad.
Rating: 
Summary: What's with all these negatived reviews?
Review: This book is written in a simple style: algoritm class description, related proofs, examples, variations and exemples. Because of this clean approach, you can basically read it in a couple days if you have the necessary background knowledge, and in a couple weeks if not. I strongly recommend this book to everyone who are calling themselves "programers", either graduated or not, it will teach/remind them what are the elegant fundamental algorithmic approches to common problems; it's seems that today's software could use a bit of this elegance. As for all the negative reviews, I'm astonished. I own several books on the subject, and I find this one the easiest to read, no question. It must be some sort of personal vendetta against the author, a failed undegraduate course with this book as teaching material, or some other personal reason; that's probably why this/these person(s) whish(es) to remain anonymous.
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