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Concrete Mathematics: A Foundation for Computer Science (2nd Edition) 2nd Edition
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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.
- ISBN-100201558025
- ISBN-13978-0201558029
- Edition2nd
- PublisherAddison-Wesley Professional
- Publication dateFebruary 28, 1994
- LanguageEnglish
- Dimensions9.38 x 7.82 x 1.44 inches
- Print length672 pages
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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 Professor Emeritus of The Art of Computer Programming at Stanford University. His prolific writings include four volumes on The Art of Computer Programming, and five books related to his TEX and METAFONT typesetting systems.
Oren Patashnik is a member of the research staff at the Center for Communications Research, La Jolla, California. He is also the author of BibTEX, a widely used bibliography processor.
Product details
- Publisher : Addison-Wesley Professional; 2nd edition (February 28, 1994)
- Language : English
- Hardcover : 672 pages
- ISBN-10 : 0201558025
- ISBN-13 : 978-0201558029
- Item Weight : 2.81 pounds
- Dimensions : 9.38 x 7.82 x 1.44 inches
- Best Sellers Rank: #65,059 in Books (See Top 100 in Books)
- #3 in Computer Algorithms
- #6 in Programming Algorithms
- #35 in Mathematics (Books)
- Customer Reviews:
About the authors

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Donald E. Knuth was born on January 10, 1938 in Milwaukee, Wisconsin. He studied mathematics as an undergraduate at Case Institute of Technology, where he also wrote software at the Computing Center. The Case faculty took the unprecedented step of awarding him a Master's degree together with the B.S. he received in 1960. After graduate studies at California Institute of Technology, he received a Ph.D. in Mathematics in 1963 and then remained on the mathematics faculty. Throughout this period he continued to be involved with software development, serving as consultant to Burroughs Corporation from 1960-1968 and as editor of Programming Languages for ACM publications from 1964-1967.
He joined Stanford University as Professor of Computer Science in 1968, and was appointed to Stanford's first endowed chair in computer science nine years later. As a university professor he introduced a variety of new courses into the curriculum, notably Data Structures and Concrete Mathematics. In 1993 he became Professor Emeritus of The Art of Computer Programming. He has supervised the dissertations of 28 students.
Knuth began in 1962 to prepare textbooks about programming techniques, and this work evolved into a projected seven-volume series entitled The Art of Computer Programming. Volumes 1-3 first appeared in 1968, 1969, and 1973. Having revised these three in 1997, he is now working full time on the remaining volumes. Volume 4A appeared at the beginning of 2011. More than one million copies have already been printed, including translations into ten languages.
He took ten years off from that project to work on digital typography, developing the TeX system for document preparation and the METAFONT system for alphabet design. Noteworthy by-products of those activities were the WEB and CWEB languages for structured documentation, and the accompanying methodology of Literate Programming. TeX is now used to produce most of the world's scientific literature in physics and mathematics.
His research papers have been instrumental in establishing several subareas of computer science and software engineering: LR(k) parsing; attribute grammars; the Knuth-Bendix algorithm for axiomatic reasoning; empirical studies of user programs and profiles; analysis of algorithms. In general, his works have been directed towards the search for a proper balance between theory and practice.
Professor Knuth received the ACM Turing Award in 1974 and became a Fellow of the British Computer Society in 1980, an Honorary Member of the IEEE in 1982. He is a member of the American Academy of Arts and Sciences, the National Academy of Sciences, and the National Academy of Engineering; he is also a foreign associate of l'Academie des Sciences (Paris), Det Norske Videnskaps-Akademi (Oslo), Bayerische Akademie der Wissenschaften (Munich), the Royal Society (London), and Rossiiskaya Akademia Nauk (Moscow). He holds five patents and has published approximately 160 papers in addition to his 28 books. He received the Medal of Science from President Carter in 1979, the American Mathematical Society's Steele Prize for expository writing in 1986, the New York Academy of Sciences Award in 1987, the J.D. Warnier Prize for software methodology in 1989, the Adelskøld Medal from the Swedish Academy of Sciences in 1994, the Harvey Prize from the Technion in 1995, and the Kyoto Prize for advanced technology in 1996. He was a charter recipient of the IEEE Computer Pioneer Award in 1982, after having received the IEEE Computer Society's W. Wallace McDowell Award in 1980; he received the IEEE's John von Neumann Medal in 1995. He holds honorary doctorates from Oxford University, the University of Paris, St. Petersburg University, and more than a dozen colleges and universities in America.
Professor Knuth lives on the Stanford campus with his wife, Jill. They have two children, John and Jennifer. Music is his main avocation.

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Material covered includes the basics of discrete math, plus some extras needed for analysis of algorithms. There is an explicit and polemical slant towards a concrete (Knuth calls it 'Eulerian') approach, but this basically just means the emphasis is on explicit calculation and motivating examples, rather than 'elegant' formality and abstraction.
In terms of topics, the book starts with a chapter introducing recurrences, then guides the reader through developing familiarity and calculational skill with sums and sigma notation; floors and ceilings; modular arithmetic and a bit of number theory; binomial coefficients and special functions, finally culminating with generating functions, which provide a general framework for solving recurrences encountered in earlier chapters. There are also a couple of chapters on discrete probability and asymptotics, which round out the stated goal of the book: covering preparatory mathematical material needed for the analysis of algorithms in Knuth's Art of Computer Programming.
As with TAOCP, the problem sets are as enjoyable and carefully constructed as the exposition, and the solutions are included in the back of the book (about 500 pages of exposition, and about 100 pages of solutions). These problems could easily keep an interested person busy for a lifetime. They are each graded using Knuth's customary scale, and range from the trivially easy to open research problems.
It's extremely dense, which is great for me because I will keep learning from it for months or years to come.
If you're relatively new to the subject, like me, a lot of this book won't be easy to comprehend the first time around, however with determination and online resources for help, you can get through it.
Even without online resources, if you keep going when you don't understand something, and try to work out the examples on paper, you will get far.
After studying this book for a while, go back to the sections that you missed the first time and they should make more sense.
Try as many of the exercises as you can, some are very difficult, but others can be accomplished the first time around.
This book is not for the faint of heart. If you aren't using it for a class, it will take a lot of dedication to make it through. That said, it's one of the best resources for learning discrete and continuous mathematics that relate to computer science.
A great precursor to many of the great algorithm books.
Take-Aways (As of Ch 3):
There are many aspects of summations, integer functions, and proofing that: I never saw covered in my CS degree, are unforgettable, and can be immediately applied to most algorithm research. Those alone make this book worth every penny. Further, the problems posed by this book are more than just repeated mechanics, as I have seen in books like those mentioned below. Each problem is carefully chosen, thorough, and exposes multiple aspects of each topic. They really do weed out many faults that I wasn't really exposed to- as a small example: the importance of ensuring validity of n-1 and n-2 hypothesis & base cases during an induction proof.
The Bad:
Students educated through a contemporary CS track at most American uni's, I believe, (e.g. Rosen Discrete Math, Cormen Algorithms) will find this book both terrifyingly terse and frustratingly paced. In many cases, examples are given without derivation. In many cases, important points are made without obvious connection to previous topics. This is not without a solution however, and getting through this book is often an acquired technique of paper noting things as-you-go, as well as a learned hyper-literacy. The terseness is also a double-edged sword, as sometimes I found it useful as an extra opportunity to practice the taught methods to see if I could come to the same result. Further, the reader should be prepared to go back and review propositional logic & university calculus theorems (atleast FTC, definite vs indefinite integrals). For example, the description of sum by parts in the section on finite calculus assumes _much_ from the reader, and being able to use university calc. as a point of reference to get through that is helpful.
A lot of exercises are tersely explained in both problem and solution. Further, many solutions are totally left-field (having little to do with material in the book). This isn't necessarily bad, as even taking the wrong path to a solution is very educational. However, at some point the reader has to make a judgment as to how long to commit to a certain problem. Many terse problems & left-field solutions instill the wrong judgment: quitting too early.
Conclusion:
Attention to detail & extra work is necessary to overcome the terseness of this particular beast, but it's worth it. I recommend this book for developers confronted with algorithm optimization problems, as a well as for a different take on parts of discrete math, and definitely for students coming out of a US state school CS program, the last which this book complements very well. Having worked through some of V1 TAOCP, I would also say that the book is effective in expanding upon its math underpinnings (V1 at-least), and incidentally, does give one confidence to tackle Knuth's other works.
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But, my only minor complaint is some of the explanations are a little "sparse". The authors draw conclusions that my mind does not see, but this can be seen as an opportunity to self research from other sources, or to give up.
10/10
Happy Reading!
この本は大学数学の本にありがちな抽象論をすっ飛ばして、いい意味で高校数学のような技のある証明方法で整数論の重要な定理を証明しています。応用例が多く、特に高校数学などで実践的に使いたくなる手法が多いです。
この本は高校生、大学生の両方にお勧めできますが、特に高校生に読んでほしいと思います。なぜなら整数と数列の発展的な学習で抽象論のない高校生向けの本はこれ以外に良い本を見たことがないからです。月刊大学への数学などで発展的な内容の記事がありますが、この本はより深い内容まで突っ込んでしかもわかりやすく説明しているため大学への数学を読みこなせる高校生にとって最適な本です。











