Rating: 
Summary: THE CS Bible? Let's be realistic and honest
Review: The Art of CP (TAoCP) book set covers the core of computer science curriculum on data structures and algorithms. Not everything there is today (that would be impossible), just the core, but that's more than enough to begin with (and for most people quite sufficient in general.) This is typical Knuth: he knows his stuff, he writes very well, he's an encyclopedic mind; his texts are mathematically rich, yet at the same time not overwhelming; time and again he demonstrates this 19-th century germanic scientific style, which is to say he's incredibly detailed and exact -- one can even accuse him of pedantry, but in a good sense. He writes with a sharp, dry wit (his sense of humour makes him unique among the rest of the writers on the computing theme.) So far so good.However, all the benefits mentioned above notwithstanding, I have to say that on balance this triptych of his is impractical. It has either become outdated, or was even originally written with an independently-wealthy reader in mind, someone like an 18th century gentleman-farmer who, fully disencumbered of the vulgarity of having to earn a living, is leasurely indulging in the exercise of his mental ability for the pure intellectual challenge of it; someone with no plebeian concerns of practicality ever entering his exalted mind. The problem is with MIX. I second what the others said about it, and what's more, I refuse to accept the explanation (purportedly Knuth's) posted below by someone: the problem is not only that MIX is an assembly language (which still would be a functional malapropism in a book like that) -- no, a far more grievous problem is that MIX is a phantasm, a whimsically extravagant invention having no real-life equivalent, at least today. The mythical processor underlying this thing (5-byte words, etc) is not something that anyone below 40 years of age has ever seen, even if it does have historical analogues. The gravamen of the offence here is not that it is some real but unfamiliar processor's assembly -- after all, if you know i86 assembly, you can (kinda, sorta) read the motorola equivalent... No, it is that MIX and the fairy-tale processor architecture it is imagined to run on are *purposely made to resemble nothing* that you may have some familiarity with -- thus making the already-difficult material obfuscated beyond anything even marginally manageable for a regular computing Joe, who has a (real) life, and at any rate, can't limit his CS intake to this one work. Elucidating difficult in itself CS material via examples in assembly language of even a real (or made-up but realistic) kind is a very bad choice because the student's attention, already taxed by the subject matter itself, will be further burdened by the non-algorithmic nature of the assembly language. But to exacerbate this potential ordeal by insisting on the use of something so gratuitously eccentric and profitless for the reader as MIX is simply unconscionable. Ideally, what a good CS text of this sort will use is pseudocode. But if a writer wishes to add to his book a realistic slant, it is acceptable that he use some sort of real language -- so long as it is algorithmic; today, C is a perfect choice. Knuth counters (and he's absolutely right): there was no C when the book was written. He's also right in saying that had he written it with Pascal it would have become outdated by now. So if that was the problem, TAoCP could have been written with some sort of pseudocode; this would last forever. Of course, even using a real language would not actually be such a great problem -- we all know of similar books where the originally-chosen language was replaced when it fell in disuse: for example the numeric programming book by Teukolsky; it started with fortran and was then redone in C; this demonstrates that the language part can be brought up-to-date if necessary. Both Fortran and C are algorithmic languages that, owing to their readability, can be used instead of pseudocode. Ideally, books should be written with both pseudocode (a must, in my view), and, in order to give an example of an actual implementation, some real language (see the recent book by Goodrich; it's pseudocode throughout and a smattering of Java here and there -- perfect!) To sum it all up: measured by today's needs, The Art of CP is overrated (out of snobbery; bragging of having read it is "kewl"; meantime, the truth is, not too many people are capable of such a feat for the reasons stipulated above; when actually used, TAoCP books are read in chunks, a chapter here, a chapter there -- which is a shame, because they are very well written, and to work through them in their entirety would be much more profitable than biting off a little here and there.) I am going to be slammed by the Knuth cult followers for saying this, but I do not recommend these books. Instead, consider something similar but more practical: two titles immediately come to mind, Cormen &Co. (a.k.a. CLR) and Goodrich (forget the title but search on the name.) Foundations of Computer Science by Aho/Ullmann (The Tortoise book) is a suitable option as well. TAoCP is potentially very good, but until someone ruthlessly excises all the bloody junk (MIX etc.) and replaces it with pseudocode or C, it will remain useless. Don't get me wrong here: Knuth is an admirable, justly venerated computer scientist, and a very good writer to boot (for example his Concrete Mathematics book is excellent). But when it comes to TAoCP, even though to mention it is very chic in some circles, we must admit the obvious: he has produced a work that's impenetrable (or, rather, the enormity of time and effort required to penetrate it makes such an attempt an unworthy investment) and therefore useless in practical terms for the majority of the potential readership.
Rating: 
Summary: Without reading Knuth you are at most a talented amateur
Review: The three volumes of the original version of "The Art of Computer Programming" are more than thirty years old now. I still have the edition I bought back in 1978 or so and they're never too far from the "easy to reach shelf" in my bookshelves. Sometimes I rearrange things and move them away, always figuring that newer books will work as well, but somehow they always move back - not always quickly, but rarely too slowly. Sometimes its because I just want to reread something, sometimes its because I want to challenge myself with one of the problems, but often enough it is because I find myself needing to supplement information from somewhere else or because I just can not find quite what I need anywhere else. And I will turn to the web to search for things - but first I usually check out TAOCP. It can be tough going in some places, the math sometimes reaching the "AAArrrggghhhh, run away, run away" kind of appearance, but a bit of work almost invariably pays off. This is not a book from which you will learn to program. You should have some facility with more than college freshman level mathematics. And you'll need to read things more than once in many cases. If you're an IT person, a software installer type, a low level coder or the like and are content with this, you can probably afford to avoid ever reading TAOCP, but if you want to solve the hard problems, if you want to learn just WHY things work, and learn the mathematics and the kinds of analysis techniques that make the difference between the grunt programmer and the really good ones, you'll need the math, you'll need the kind of information, knowledge and computerology-goodness-and-niceness that TAOCP (and few books other than TAOCP) can give you. Seeing a well used copy of TAOCP on a computer professionals bookshelf is always a sign to me that they're serious about their profession and about their own learning. Not seeing one is often a flag that they're someone I'd rather not have on a project I'm involved with. Worse yet not seeing TAOCP on a CS professors bookshelf leads me to the impression that professor is at best semi-educated, and at worst one of those frightening types who managed to slip through the cracks somehow. Now I'm waiting for Volume 4 (and all the rest). (Interestingly, I got one of those mail back cards from the publisher about 4 years ago asking me if I wanted to reserve a copy of the "soon to be published" V4 - I could not resist calling and asking lots of details about it.) I was also lucky enough to find copies of the original editions of V1 and V3 two years back in a booksale for a grand total of about a dollar. Now now I have 1.101010... (in binary) sets. If V1-4 get published in a boxed set I'll undoubtedly spring for the set at whatever price.
Rating:
Summary: Are you serious about algorithms?
Review: These are really great books. If you are serious about algorithms and you are serius about data structures than this is a book you are looking for. But you should be Intermediate level programmer to read these books. Chapter on sorting is really a great one. Knuth has done a great job on this chapter.
Rating:
Summary: This is the best programming book ever!
Review: These books are a must for programmers. GET IT!!!!!
Rating:
Summary: Excellent, for certain people!
Review: These books are indisputably classics of the field, and like all classics they have religious adherents and equally firm detractors. The key difference between the two groups is that the adherents are interested in computer SCIENCE, whereas the rest are more taken with computer programming. The books are well written, quite mathematical, and abstract. The books deal with the core subjects of computer science and shy away from the trendy, and so some people tend to see them as anachronistic. Nevertheless, they are deservedly core references in computer science, and a joy for any patient, theoretically minded reader. There are three points I believe should be made. 1) a lot of the detractors of the books are saying correct things: the books don't deal with hot topics, they do present things in greater detail than is necessary in day to day programming, they are books they require a lot of the reader. What they don't recognize is that this is the intention, and that there is nothing wrong with that. The book is targeted at those with a geniune interest in theoretical computer science. 2) many reviewers complain about Knuth's typesetting system, TeX. What they fail to recognize is that TeX is incredibly useful, and about as user friendly as could be expected, for the task for which it was designed: typesetting professional quality mathematics. Anyone who challenges this statement would have to contend with virtually the entire community of people who write papers using higher mathematics, including virtually all professional physicists, mathematicians, and computer scientists. 3) some people accuse Knuth's books of being poorly written. These people are ignorant: either they have not read the works, or they would not recognize skillful writing if they saw it. These books are splendid examples of scientific writing, and are justifiably acclaimed as such. In short, Knuth's books have ensured that the word "science" deserves its place in the phrase "computer science"
Rating:
Summary: outstanding
Review: these books constitute the definitive collection of the fundamental concepts of computational algorithms and data structures. the discussions of sorting and search are particularly good. the amount of historical material is also outstanding.
Rating:
Summary: The Best Algorithm Books in Computer Science
Review: These three books are amazing. A deep, definitive coverage of the theoretical basis of computer science. In fact, to the extent that computer science is a science, you should refer to these books, if you are ever in doubt. As a measure of how well regarded these are, Knuth mentions in his home page that American Scientist magazine ranked this amongst the top 12 scientific monographs of the twentieth century, alongside books by Einstein, Dirac, Pauling and Feynman. Much of computer programming and usage today builds upon the algorithms described in the books. What does it mean to have a "good" random number generator? What are quantitative tests for randomness? How can you efficiently sort a list? How do you find the greatest common factor of two (large) positive integers? It is true that the typical computer programmer does not know most of the material in the books. This is because she usually can access subroutines that come with the language or are in standard libraries that implement the core algorithms. For example, in Java, there is a routine called Collections.sort(), which you call with the name of a list in the brackets, and the routine will sort it. But within the field of computer programming, sometimes you may be called upon to implement those core algorithms. So what do you do? Turn here for help. The books are also graced with a vital attribute. Each section of a chapter has a set of questions. Typically these are tough; they can keep you busy indeed. Plus, Knuth supplies the answers. The combination is a great learning experience. So often have I wondered at textbooks that don't supply questions. Students need hands on experience.
Rating:
Summary: Beyond extraordinary
Review: This is a work of surpassing beauty, akin to Beethoven's Fifth. This book introduced me to the joy of computer science and still fills me with wonder that one man could do so much.
Rating:
Summary: A Classical & Definitive Work
Review: This is the foundation of any computer scientist's library. While certainly NOT light reading, the wealth of information contained in these volumes is relevant to a variety of real world problems in computing. While few people may be willing to commit the time and effort to read all three volumes, those who do will find themselves among the most informed and fully grounded professionals in computing today.
Rating:
Summary: A Classical & Definitive Work
Review: This is the foundation of any computer scientist's library. While certainly NOT light reading, the wealth of information contained in these volumes is relevant to a variety of real world problems in computing. While few people may be willing to commit the time and effort to read all three volumes, those who do will find themselves among the most informed and fully grounded professionals in computing today.
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