Rating: 
Summary: Rigorous coverage of the most widely used algorithms
Review: I personally bought this book in preparation for the International Olympiad in Informatics (IOI), and it helped me immensely in getting off the ground with the algorithms I had to learn, especially the chapter on Dynamic Programming. Since then, however it has remained a priceless companion during my studies and at home.This is the definitive reference for algorithms with a firm theoretical and mathematical foundation. Algorithms are treated with a thorough theoretical introduction often with a complete mathematical walkthrough, a clearly thought out solution, a discussion of its pros and cons, lots of clear and consisive diagrams, a pseudocode implementation, and a good deal of serious optimisation discussion. It's written in an accessible manner, starting with the elementary issues, progressing to the advanced and complex thinking needed to conquer them, so you'll find you have to give it your full concentration. This book will not disappoint. Its explanations are rigorous and its coverage spans all the general purpose algorithms with little focus on their applications but rather on the algorithms themselves. The book covers such major areas as sorting, data structures, advanced design and analysis techniques, graphs, each about a hundred pages on average, and a selection of specialised algorithms such as parallel programming, string matching and computational geometry. Because these algorithms are used everywhere, from games, graphics and simulations to electrical engineering it will have a broad audience and will find a home almost anywhere there is serious programming involved. Each chapter is a unit in itself which means you don't need to read it cover to cover, since they all start off smoothly and handhold you through. Clearly written by professionals, this is the book I know contains the information that I can't find elsewhere.
Rating:
Summary: Theoretical Foundation
Review: I would just like to add a couple points to the review of this book here. First, it is a great introduction to the theoretical foundation of algorithms and computation, and it is not your average algorithm cook book. For that, you can find numerous books on various topics, such as "Algorithms in C" or "Numerical Recipes." Second, the assertion that it is processing power, not code optimization that reigns these days is simply missing the point. It is first of all not true, (just ask any programmers working on games, or serious business processing, or databases, or networks -- you name it -- code optimization is as important as ever; maybe your run of the mill GUI front end needs no optimization, but you wouldn't care about algorithms there anyway). And if you read the book, you will know that a lot of important problems only have exponetial solutions, and exponetial growth in hardware power (aka Moore's law) has a physical limitation. Therefore don't expect improvment in Intel chips to compensate for all of your bad programming. Third, this book pretty much only deals with asymptotic behaviors of algorithms. If you want to learn code optimization, it's by far not enough. You have to optimize the code behavior in each iterative cycle as well, such as reducing the number of comparisons, reducing memory references, reducing floating point multiplications and division etc. However, there seems to be no book on how to reduce such "constants" in algorithms. "Real-world" optimized code often involve techniques that's system dependent, or that uses information/boundary conditions that are not part of the general problem etc. There is no better teacher other than reading some good code or having a discussion with the field warriors - good programmers around you. In summary, for its purpose - a relatively theoretical treatment of basic algorithms, this book is the best I have seen.
Rating:
Summary: Honestly? I'm disappointed with reviewers...
Review: Giving this book a bad review because:
a) you had a bad instructor for the course
b) you find the material difficult
c) you can't understand pseudo-code are not what I would call constructive or worthwhile critiques of the text of this excellent book. PLEASE society, PLEASE understand that some topics you have to actually WORK at understanding. It won't be spoon fed to you. It seems moreso with Computer Science majors than other majors (I'm an electrical engineer undergrad, comp sci grad student) that they whine and whine and whine about the math or about it being difficult to actually have to work to understand something. Oh my GOODNESS!!!! It's hard? Well, BLAME THE BOOK. Rant over. This book is amazing. It's the bible of algorithms and, to some extent, data structures. If you're not aforementioned whiners, feel free to buy this book, work hard, and learn a lot! There's not a better book out there in my experience.
Rating:
Summary: Amazing
Review: I'll just start out by saying that this is probably the best computer science related book that I have read, and I've read a lot during by education and beyond. This book covers so many important data structures, algorithms, and concepts, and it does a great job with everything. Everything is easy to read and well-explained with just the right amount of illustrations and pseudocode examples. Each section and chapter also includes exercises which use information from the material very well. The size of this book and some of the topics might scare some people away, but I would recommend it for those new to algorighms and data structures,to those who may not be familiar with some of the concepts covered in the book, or to those who haven't and/or don't want to memorize all of the intricacies of, say, Fibonacci heaps.
Rating:
Summary: What every computer scientist should have
Review: If one were to make a list of the 100 best books in computer science, then winnow that list down to 10 books, and then again down to 1 book, surely this would be that book. Known in computer science circles as CLR (for the authors) or simply, "The White Book", Introduction to Algorithms by Cormen, Leiserson, and Rivest is the de-facto standard text for algorithms and data structures. It covers all the basic subjects (big-O notation, trees, graphs, etc...) as well as a few intermediate subjects (amortized analysis, matroids, etc...). Of course, this book is not the be-all and end-all of computer science nor does it pretend to be. It touches on NP-completeness only lightly and all but omits randomization; but if you wanted a text on NP-completeness, you would be reading Garey & Johnson and if you wanted randomization you'd go to Motwani & Raghavan. But if you need a reference on data structures and algorithms, this is the book for you. Now, some have complained that while this book is an excellent reference that it is a poor text to learn from. I beg to differ. I concede that it is certainly more demanding than many other introductory texts, but this is a boon not a curse. By remaining true to computer science's mathematical heritage, Cormen et al. force the reader to become accustomed to rigourous, formal reasoning, something which is unfortunately absent in many computer science curricula. The authors present the concepts cleanly and clearly, without the distraction of any specific programming language/paradigm. Perhaps it is this removal from a familiar C/C++/Java/flavour-of-the-month/etc... milieu which makes some readers nervous. But it is precisely this separation which forces the reader up into the realm of abstraction where computer science truly resides.
Rating: 
Summary: Poorly written with lack of ways to test yourself
Review: While many have noted how Thomas Corwen and his co-authors have added a scholarly touch to this subject with plenty of proofs it does not make for a good text. One can argue that this book should supplement the instructor's teachings. That would be fine except for the fact that there are no answers to the problems. Therefore, a student has no idea if he or she is on the right track.
To this end Corwen snidely replies on his website that any student asking for the answer will have his or her name posted as a potential cheater since Corwen believes that instructors should be able to use his problems as homework. Here's an idea, how about instructors developing their own problems!
Corwen also does not relate the material in plain English as someone like Frank Carrano does. There are other sources of many of the concepts like binary search trees, sorting algorithms, O-notation. The only thing Corwen is adding is lots of proof and mathematical shorthand.
If you are interested in the mathematical concepts behind the algorithms this is a fine introduction. If you are interested in the algorithmic concepts, this is not for you. Ultimately if you are a student whose instructor will be using this book, you have no choice about buying it. If you are an instructor, however, look at another book to supplement your teachings.
Rating:
Summary: THE book to introduce algorithms
Review: You shouldn't have to read this review... this book is unmatched in it's field - it's a great book for someone with no background in algorithms to start learning. The exercises are very interesting with some being more mathematical while others are thought provoking extensions to material covered in the book. It's easily the bible in this field. After this one can go on to more advanced specialized material like Papadimitriou, Motwani and Raghavan etc. If you don't have this book and you work with ANY kind of algorithms or do any kind of programming, you owe it to yourself to get it.
Rating:
Summary: More than excellent
Review: It is a book that deserves more than five stars. Hard stuff, yet it is presented in a way that you get right virtually by reading. Very concise, every page very line counts.
Rating:
Summary: Great book
Review: The material is very hard, but the book is written in a way that makes it as easy to read as possible. There is TONS of information here. I usually like to highlight the important stuff when I read, but in this book, nearly everything is important and worth highlighting. In other words, there is no B.S.; they get right down to the point.
Rating:
Summary: Good coverage
Review: This book delivers what every programmer
should know. 1) How to reason,analyse,determine algorithm efficiency
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