Rating: 
Summary: Complete, but examples are poor
Review: I used this book for an Algorithms and Analysis course. While the book does present several interesting algorithms and is very complete, it has some major problems as well, namely with the examples. The book breaks a few of the standard rules I've learned in all other computer science courses. Every other CS course I've has emphasizes that computer scientists count from 0, not 1, when using loop control variables. However, this book ignores that practice and counts from 1. Also, every other CS course has emphasized using descriptive variable names. The pseudocode examples in this book almost always use single letters as names. These two issues combined make the examples clumsy; the reader often has to spend more time figuring out what the variable names mean and adjusting intuitive loop counting than understand how the algorithms work. This book contains a great deal of useful information, but it could be presented more clearly.
Rating: 
Summary: Disappoiting
Review: Not very rigorous, often confusing. More quantity than quality.
Rating: 
Summary: The Best Single Book on Algorithms
Review: ...This is easily the best single book on algorithms. It does several different things well. Each topic is covered in increasing level of theory. That is, when it gets too theoretical for you, move on to the next area. If you do not like the proofs, no one is forcing you to read them. There are mini-courses spread around in the text; for example there is one on number theory and another on probability. These courses are well done; however given their concise nature, they are more useful as reviews than introductions. This book does require some mathematical maturity, but it is very much an undergraduate text though I myself have taught out of it at the graduate level. The writing of the algorithms in pseudo-code is as clear as I have ever seen. At the end of each section is a nice summary of the literature for that area. There are sufficient examples and the general writing quality is of a very high caliber. Note that this review refers to the first edition.
Rating: 
Summary: Thorough....But Hard to Follow
Review: This is "the book", you know. It has all the stuffs you can think of related to computer science, but not specific to a certain field. Searching, sorting, data structres, time analysis, space and time trade-offs, practicality...you name it. The book has it! And best of all, the book is language independent. It doesn't show codes in C++ or Java like many CS books. Instead, it uses pseudocodes. And the only problem I have with this book is those pseudocodes! They are really hard to follow. They could use some more English rather than using a lot of mathematical symbols. Pseudocodes are invented so that we could write some of our codes in English, you know. You will find yourself reading those pseucodes again and again because you just couldn't understand them. Oh well, this is not a book for the coffee table any way. This is one of the books you must have if you call yourself a serious programmer or "Computer Scientist". One of the Best! Complete and Thorough!
Rating:
Summary: Academic, not practical.
Review: This is by far the best introduction to algorithms I have seen, if you are a Computer Scientist with interest in inventing new algorithms and proving their merit mathematically. If you only want a catalog of algorithms to use for implementation, purchase a smaller and less expensive text.
Rating:
Summary: A Well Rounded Text
Review: In addition to the typical collection of algorithms for sorting and graph manipulation the book contains algorithms for parallel computing. Time complexity and NP completeness are also well illustrated. Time complexity is explained with worked out examples as well as easy to understand theoretical descriptions. In sum, this book should be a standard for every programmer's reference shelf.
Rating: 
Summary: Extensive, but some problems
Review: CLR's Introduction to Algorithms is, for the most part,excellent. The primary annoyance is that the text is now at least inits nineteenth printing, and they have not incorporated the 27 pages of errata (i.e., typos and bugs) found since the second printing.
Rating:
Summary: The best of its kind
Review: This is certainly the best book on algorithms and data structures that I know of. Each chapter presents a different type or set of problem(s) and the data structures and methods that are necessary to solve these problems. After reading this book, one will know the benefits of one data structure to another, and when to use one and not the other. The proofs that are supplied are often lengthy, but one is capable of getting a lot out of the book without necessarily understanding all the proofs. One of the drawbacks is that the book does not include data structures that have been discovered over the past ten years, since the book is a decade old. Skip lists are one data structure that comes to mind. Readers are encouraged to supplement this book with more recent material. For teachers, this book can serve as the text for a course in data structures or algorithms; there is a clear point at which the text becomes more based on algorithms like the Traveling Salesman problem, Dijkstra's algorithm, Prim and Kruskal, et. al, which should perhaps me moved to a second course.
Rating:
Summary: A landmark in the study of algorithms
Review: This book is simply the best for understanding why and how of algorithms. This book only brings in math essential for understanding the algorithms and how they really work. If you do not care how an algorithm works, but are only looking for source code in Java or C++ this books is NOT for you. Personally, I find the book a joy to read because of the depth and breadth of the book. I would have liked to see the answers to the problems included in the book.
Rating:
Summary: The best textbook I have ever seen
Review: I was the instructor for a junior/senior course on Algorithms at the University of Southern California and I used this book as the textbook. Unfortunately, many of the students didn't like this book because they did not appreciate the mathematical flavor of the book. A course on Algorithms is useless without a sound background in discrete mathematics. Hence, this book assumes that you are reasonably strong in Discrete Mathematics. I haven't seen a better textbook ! Here are some reasons: 1. The discrete mathematics foundations are present in the first few chapters of this book and so, you can quickly brush up on any discrete math background that you may require while using this book. 2. The style of writing is very light and at the same time, rigorous - almost as if you are in the middle of a lecture while reading the book. 3. The material is comprehensive and serves as an excellent reference for other courses and in your future career. 4. The exercises and problems provide a very good learning experience. 5. It's a good-looking book !
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