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I purchased this book for a college course. It came in plenty of time for school.I will always buy school books first from amazon. I will not pay full price for a book that is almost in perfect condition. Amazon is a great way to buy books.
The algorithms uninteresting. I took this class as a student and I was not impressed at all by the text. The historical content was far too sparse. The text is far too informal. The problems unchallenging. If you are going to have history, have enough that it satisfies or have none at all. I would recommend "How to Think About Algorithms" by Jeff Edmonds over this book any day.
I wouldn't suggest it as a starters book by its own though. The typical CS student enters the world of algorithms via data structures, search and sort, shortest paths, graph algorithms, etc. This is one of the best algorithms books out there. I had great fun reading this book, even though I have studied most of these individual areas before. The book tells you from the start that this is not your traditional algorithms book. Many of the topics it discusses have introductory books of their own with more details, such as graph theory/algorithms, numerical algorithms, linear programming, randomized algorithms, quantum algorithms, theory of computation, etc. This, in my opinion, is one of the great virtues of the book.
I strongly believe that a CS graduate should be familiar with all the topics discussed in this book, may be with the exception of the chapter on quantum computing. What I like about it is the breadth of the topics discussed. Some students end up with a very limited view of the field. What amazes me about this book is how it puts all these things into perspective. The book does not delve into rigorous proofs, but rather gives the crux of the proof in most of the cases. I really like the subject of the first few chapters which lead to the RSA algorithm.
I am in the unfortunate situation of being in my first Algorithms class using this as our sole textbook. For that alone, I might consider keeping this book at the end of the semester. While this textbook does gloss over the subjects I need to know, for each chapter in the book only the most basic of examples are given, and each chapter makes constant references to chapters and pages well before it, so much flipping back and forth is done to grasp a concept (to understand what we're doing in 3.4, please look at the diagram in 2.3, for example). And while the chapters cover the very basics of a concept, the problems at the end of each chapter often start right off with questions not even remotely covered in the chapter, taking stuff to a level I can't even begin to grasp as of yet.The only reason I didn't give this book 1 star is because I think this book might be good for a refresher of Algorithms for someone who'd already learned them and needed to brush up. This seriously strikes me as one of those textbooks written by the grad students and barely glanced at by the professors credited with it. Seems to be a reoccurring theme in my academic life.
A very well written book. I used it for an undergraduate algorithms course I attended.It covers a big range of subjects(which i list since I see no preview possibility provided):- algorithms for numbers- divide & conquer- algorithms for graphs- greedy algorithms- dynamic programming- linear programming- reductions- NP completeness- quantum algorithmsA big plus: the writers really try to give the intuition behind the proofsI definetely recommend it.
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