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Concrete Mathematics: A Foundation for Computer Science (2nd Edition) 2nd Edition

4.6 out of 5 stars 56 customer reviews
ISBN-13: 078-5342558029
ISBN-10: 0201558025
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Editorial Reviews

From the Back Cover

This book introduces the mathematics that supports advanced computer programming and the analysis of algorithms. The primary aim of its well-known authors is to provide a solid and relevant base of mathematical skills - the skills needed to solve complex problems, to evaluate horrendous sums, and to discover subtle patterns in data. It is an indispensable text and reference not only for computer scientists - the authors themselves rely heavily on it! - but for serious users of mathematics in virtually every discipline.

Concrete Mathematics is a blending of CONtinuous and disCRETE mathematics. "More concretely," the authors explain, "it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems." The subject matter is primarily an expansion of the Mathematical Preliminaries section in Knuth's classic Art of Computer Programming, but the style of presentation is more leisurely, and individual topics are covered more deeply. Several new topics have been added, and the most significant ideas have been traced to their historical roots. The book includes more than 500 exercises, divided into six categories. Complete answers are provided for all exercises, except research problems, making the book particularly valuable for self-study.

Major topics include:

  • Sums
  • Recurrences
  • Integer functions
  • Elementary number theory
  • Binomial coefficients
  • Generating functions
  • Discrete probability
  • Asymptotic methods

This second edition includes important new material about mechanical summation. In response to the widespread use of the first edition as a reference book, the bibliography and index have also been expanded, and additional nontrivial improvements can be found on almost every page. Readers will appreciate the informal style of Concrete Mathematics. Particularly enjoyable are the marginal graffiti contributed by students who have taken courses based on this material. The authors want to convey not only the importance of the techniques presented, but some of the fun in learning and using them.

About the Author

Donald E. Knuth is known throughout the world for his pioneering work on algorithms and programming techniques, for his invention of the Tex and Metafont systems for computer typesetting, and for his prolific and influential writing. Professor Emeritus of The Art of Computer Programming at Stanford University, he currently devotes full time to the completion of these fascicles and the seven volumes to which they belong.


Product Details

  • Hardcover: 672 pages
  • Publisher: Addison-Wesley Professional; 2 edition (March 10, 1994)
  • Language: English
  • ISBN-10: 0201558025
  • ISBN-13: 978-0201558029
  • Product Dimensions: 7.6 x 1.4 x 9.4 inches
  • Shipping Weight: 3 pounds (View shipping rates and policies)
  • Average Customer Review: 4.6 out of 5 stars  See all reviews (56 customer reviews)
  • Amazon Best Sellers Rank: #60,208 in Books (See Top 100 in Books)

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Customer Reviews

Top Customer Reviews

Format: Hardcover
I have the First Edition and came here to look into the Second Edition. There are several negative reviews and basically those folks have fundamental misunderstandings. So I'll add my review.

First, what kind of book is it? It is not an introductory-level math book with lots and lots of repetition. It is a book on hard math, done in a concise manner by brilliant teachers who assume students are very comfortable with calculus, probability, etc. You really cannot afford to skip around and dabble as if this were an introductory algebra course or something. (I'm not being elitist. I did not attend Stanford and don't consider myself a math genius and am not making this a "we versus the unwashed masses" issue, as I have really struggled with the material myself.)

Second, what is the book about? Several reviewers have theories on where the "Concrete" part of the title comes from, but the bottom line is that it's a book on the discrete math that you need to know for theoretical computer science. (For example, discrete calculus versus the continuous calculus we all learned in school.) Any Analysis of Algorithms course, for example, will confront you with recurrence equations and lots of discrete math.

Third, how is the book organized? At first, it appears rather disjoint. The authors have a sort of, "Hey, look at that flower," and "hey, look under this rock" kind of approach as you walk down a path but the path itself isn't really spelled out. None-the-less, the book does build step-by-step from examples of recurrence equations (Towers of Hanooi, Josephus) in Chapter 1, to Generating Functions in Chapter 7.

Perhaps they could have made the path more explicit, but I can't see how they'd organize it much differently.
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Format: Hardcover
What is "concrete" math, as opposed to other types of math? The authors explain that the title comes from the blending of CONtinuous and disCRETE math, two branches of math that many seem to like to keep asunder, though each occurs in the foundation of the other. The topics in the book, such as sums, generating functions, and number theory, are actually standard discrete math topics; however, the treatment in this text shows the inherent continuous (read: calculus) undergirding of the topics. Without calculus, generating functions would not have come to mind and their tremendous power could not be put to use in figuring out series.

The smart-aleck marginal notes notwithstanding, this is a serious math book for those who are willing to dot every i and cross every t. Unlike most math texts (esp. graduate math texts), nothing is omitted along the way. Notation is explained (=very= important), common pitfalls are pointed out (as opposed to the usual way students come across them -- by getting back bleeding exams), and what is important and what is =not= as important are indicated.

Still, I cannot leave the marginal notes unremarked; some are serious warnings to the reader. For example, in the introduction, one note remarks "I would advise the casual student to stay away from this course." Notes that advise one to skim, and there are a few, should be taken seriously. All the marginal notes come from the TAs who had to help with the text, and thus have a more nitty-gritty understanding of the difficulties students are likely to face. Still, there are plenty of puns and bad jokes to amuse the text-reader for hours: "The empty set is pointless," "But not Imbesselian," and "John .
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Format: Hardcover
This book is excellent (5 stars) if you have the mathematical "maturity" that it assumes. If not, it will vary from 4 stars to 0 stars.

The problem is, the book looks as if it might be an entry level text and it is tempting to think that with a little extra hard work any intelligent, reasonably well-grounded mathematics undergraduate student could prove that he is a genius by mastering the content. A fair number, of course, will do just that. But many more will unnecessarily bloody their noses and egos.

Most people skip prefaces but this one shouldn't be skipped. The preface says that most of the people who have taken the course that the book is based on have been graduate students and alumni and (some) have been juniors and seniors.

To give an example of the difficulty an unwary student might find: The chapter on probability looks straightforward and well-written and it is! But it is truly useful only to students who have already studied probability theory and mastered the basic theory. The trap is that the book does, in fact, provide introductions to most of the topics covered. But in reality, they are reviews, introductions to the symbols and notation to be used and repositories for results that will be referenced throughout the book.

The prerequisites for having a profitable encounter with this book are : a good understanding of elementary number theory, probability theory and linear algebra and two years of calculus with a very good understanding of infinite series. A good knowledge of generating functions and recursive functions is also necessary. A few juniors and seniors will always be dedicated and smart enough to achieve this level of maturity but it usually takes more than four years.
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