Algorithms Books

Volume 2 of "The Art of Computer Programming" is about random numbers and also about relearning one of the three Rs from grade school, viz. arithmetic. Each topic gets one chapter.

When you generate random numbers in Excel, or VBA, or Perl, or C using functions packaged with the software, you are really using a deterministic algorithm that is not random at all; the results do however look random and so we call them "pseudorandom".

Chapter 3 contains four main sections. First a section devoted to the linear congruence method (Xn+1=(aXn + c) mod m) of generating a pseudorandom sequence; with subsections on how to choose good values for a, c, and m. Second we get a section about how to test sequences to find if they are acceptably random or not. Third we find a section on other methods, expanding on linear congruence. Finally in a particularly fascinating section, DK provides a rigorous definition of randomness.

I haven't looked much at chapter 4 yet, on arithmetic. In it Knuth covers positional arithmetic, floating point arithmetic, multiplication and division at the machine level, prime numbers and efficient ways of investigating the primeness of very large numbers.

Again, DK is thorough and methodical. Again this is not a for dummies book. Again it is about theorems, algorithms, mechanical processes, and timeless truths. Again the exercises are a fascinating blend of the practical (investigate the random generating functions on the computers in your office) to the mathematical (he asks readers to formally prove many of the theorems he cites). And yes, again Knuth uses MIX, that wonderfully archaic fictional 60s machine language. But that should not stop readers; I use Perl.

Vincent Poirier, Tokyo

I recently modified a program I wrote so that it would do operations on polynomials with multi-precision coefficients. For this, I turned to Knuth. This 3-volume set is a great starting point for learning how to implement mathematical calculations on a machine.

Don't listen to the "Reader" from CA. This person obviously has a bone to pick with Knuth. Maybe (s)he failed one of his classes. Maybe (s)he should write his/her own book on the subject.

Of course this is a classic programming text, but the book is fascinating from a mathematical point as well. The discussion of random number generation is worth the price alone. Also neat is the discussion of why numbers with lower initial digits are 'more common' in practice than those with higher initial digits, a topic I've never seen treated elsewhere.

This book is the bible of coputer programming

It contains algorithms on pseudo-random sequences, algotithms on aritmetic operations on number, matrices ect.

The only drawback of this book is that all algprothms are writeen in MIX - some kind of assembler, that make them hard to read.

This book offers a stringent treatment of random number generators and algorithms not found anywhere else. It is particularly valuable for those that deal with encryption and the analysis of cyphers. The exercises add admirably to the text. References to other books in the field are extensive. The book is written in a non-wordy, but still very readable style, making it accessible to serious computer scientists at all levels. A mathematical background is necessary.

I used the source code in this book when I implemented buddy system in my OS.
Bruno's code is very effective and the design is excellent too.
I've learned a lot of things in this book.
So, I'd like to recommend this book absolutely!

I think I said it all right there. Great for intermediate/advanced c++ users. It also contains sections on various algorithms which implement many of the data structures discussed in previous chapters. Just get the book already!

The book has a detailed introduction and explanation to the subject and clearly explains how to analyze and implement in programming. This is done all in C++ and it is suited to students in Computer Science Courses. The exercises at the end of the chapters are quite useful.

Believe the summary...this book is for 2nd and 3rd year post-secondary students. I am an experienced C++ programmer, but Grade 12 math isn't enough to cut through the explanations to get to the code, which I can understand perfectly well.

Who should buy this book? Students with a good grasp of basic calculus, who want a thoroughly academic treatment of algorithms in C++ in order to pass Computer Science.

Who should not? A C++ programmer that wants clear, effectively presented information on implementing standard algorithms and data structures in order to get their project done.

I'm of the Keep It Simple school of thought, and the practical theory and implementations in this book could have been presented much more effectively without the adademic bafflegab.

I am currently working on my calculus skills in my spare time, and as my familiarity with the mathematical notation grows, I may be able to put this book to good use. Untill then I wish I'd bought something else, programming doesn't need to be as dense as this book makes it.

This is a great book for one who has had a formal study of undergraduate Calculus/Algebra and a very good understanding of the C++ language. The book starts off with explaining the fundamentals that will be applied to measure the effectiveness of a piece of code, and is very helpful for those who wants to understand the basic theory applied in the later chapters. This books treats almost all the basic data structures and have been presented in a very simple non-profounding way, like keeping the class design and hiearchy the same throughout. All the data structures have been explained using the (easy to use) arrays as well as link-lists. This makes it easier for a novice to grasp the fundamentals and go on to implement more complex and effective data structures using link lists. Overall, I found this book extremely helpful in getting a sound footing on this topic.

It is hard to imagine any single person creating such a comprehensive, detailed, and beautiful book. Dr. Samet, do you ever sleep?! This book is not only far and away *the* reference for spatial and metric data structures, it covers many related topics as well -- and sets a very high bar for technical works of any type. A codification of all the work in an incredibly important area that is -- can you imagine? -- just plain *fun* to read.

A stunning 1000 page encyclopedia of spatial, multidimensional, and metric data structures and algorithms presented in the Knuth tradition. The general coverage is broader than an older, now out of print and expensive: "Design and Analysis of Spatial Data Structures". In a surprise, the new book is not only the size of a telephone directory, but it has double the number of useful pages. 4 extensive chapters cover data structures and algorithms for: points, objects and images, intervals and small rectangles, and the same data types in higher +dimensions. Within each chapter, the algorithms and clearly presented and are accompanied by an extensive use of figures. The algorithms which run from the expected to the exotic are summarized by the table of contents at the publisher's web site. Unexpected algorithms are also covered including: nearest neighbor finding which is useful for clustering applications, image pyramids, and object pyramids or hierarchies such as R-trees.


The book has a textbook flavor with exercises at the end of each section where specifics are left for the student; however, solutions and pseudo-code for many of the exercises are in a 300+ page appendix maintaining the book as a useful reference. This book is comprehensive, inexpensive, and in my mind - a must have.

The best possible scenario for a reader buying a tech book is to have

1) a single author, rather than an "editor" so the conceptual presentation and perspective of the product is consistent throughout

2) an author that knows the field inside out and can speak and think about it naturally with no hint in the presentation that he or she has hit upon a topic they're shaky with, and needs to resort to "high concept hand waving" to skate over the subject.

3) an author whose command of language is first rate - precise without being pedantic, and whose tone and level of exposition remains consistent throughout.

4) an author who spares himself nothing in terms of effort, cuts no corners and leaves nothing out for the student to "fill in" when explaining difficult concepts.

In this book, you get all that and more.

It's an encyclopedia of multi-d DS, written by a top researcher in the field, and addresses the subject matter at every level, from the panoramic to the implementation details. This book is on par with Jim Gray's near-perfect Transaction Processing.

If you think you don't need to know the subject matter in this book, you might want to think again. If you're developing anything that needs to find, index or classify information of any sort, graphic, text or otherwise and you're developing the basic technology, then this book is going to pay you the following dividends:

-save you time by getting you firmly grounded in the field,
-confirm and elevate your existing approach,
-make you aware of approaches, concepts and results that you just can't live in ignorance of and succeed.

Hanan Samet, the world-reknown authority on multi-dimensional data, has written a comprehensive and stunningly beautiful book. The illustrations that appear in the margins of almost every page serve to wonderfully augment the text and convey the essence of the topic under discussion. If you enjoy the clarity and broad coverage of Knuth's classics, or the elegance and wonder of Tufte's monographs, you will love this book.

Samet has distilled a lifetime of work understanding the algorithms of others and inventing major new algorithms and data structures into this very readable survey. The annotated bibliography and multiple indexes are amazing accomplishments in their own right. The book is very reasonably priced, making it accessible. This delightful book deserves to be on the bookshelf of every computer science scholar and programmer. X. Hao is right: this is truly a masterpiece.

The most complete book on the subject to date. In addition, to the huge amount of information covered, it also contains a thorough bibliography with over 2000 entries. The author uses an algorithmic approach with plenty of pseudo-code without resorting to complicated mathematical formulae. Clear explanations are given with more than 450 figures illustrating the ideas. The result is a wonderful place to explore spatial, multidimensional, and metric data structures on one's own or as part of a class. It has more than 1200 exercises that test the readers' understanding of the covered material, while many also develop the material in the text further. Solutions are provided to most of the exercises and also contain detailed pseudo code for many of the representations. The book is easily accessible to a wide range of readers who need not be programmers or computer scientists. Sample pages for the opening discussion in each of the book's four chapters are available at the publisher's web site.

This book goes far beyond Hanan Samet's previous books containing completely new material such as a thorough discussion of image- and object-based representations, as well as an entire chapter on high-dimensional and metric data representations which together comprise almost two-thirds of the book. In addition, the new book expands considerably the discussion of point data in his out of print book titled "The Design and Analysis of Spatial Data Structures," which though still contains some material that is not in the new book. The new book has no overlap with his other out of print book titled "Applications of Spatial Data Structures: Computer Graphics, Image Processing and GIS".

To summarize, this is another wonderful book from the most respected authority in the field. From novice to expert, everyone can learn something from this true masterpiece.

For a long time analytic combinatorics lacks a good and comprehensive textbook. Almost every learner in this field learns this subject via scattered papers and chapters in different books or journels. The apprearence of this book is so welcome by learners and researchers that it offers a excellent introduction of this powerful and relatively new field. Flajolet and Sedgewick are the famous masters of this field, and this book proves that again. The writing style is succinct, with instant exercise(s) after every important concept and result. The pace of this book is very natural and self-contained. The first half of this book deals with the basic tools used for analysis of algorithm, from the recurrence, generating function, to asymptotic approx. Then it discusses 2 most crucial subjects: trees and permutations. The last 2 chapter turns to strings and words. I found it very readble that there is a typical and core example in every chapter. BTW, since I still haven't finished studying this book, but I must say that Chapter 5 (Asymptotic) is among many textbooks the best introduction to this hard topic so far.

This book is REALLY for coursework : someone who is going to sit down and read and work thru this book sequentially, not randomly like a reference book.
Other than that caveat it does what it promises ably but be aware that it is MATHS heavy and REQUIRES the programme work.

I read a lot of books about complexity analysis. And this book is a state of art in the field. Easy to read, and well done.It cover the necessary staff that every new commer to the field should know, can be used as a refference,and it make a good teaching material for graduate student.

I don't know whether the style of this book is good or not but for me the chapter on generating functions was very readable. At the time of reading I already have read several books for the understanding of generating functions; including Graham, Knuth, and Patashnik's "Concrete Mathematics," which is definitely great but difficult to me. I've got a solid understanding of the subject through two books: Polya et al's "Notes on Introductory Combinatorics" and Sedgewick and Flajolet's.

This is an excellent book on the analysis of algorithms. More specifically, it is a book on the mathematics needed for the analysis of algorithms. Quite a few algorithms are presented and analyzed in great detail, but the emphasis is on the analysis techniques rather than on the algorithms.

This is in contrast with Cormen,Leiserson and Rivest, or Sedgewick's own "Algorithms" series which emphasize the algorithms rather than the analysis.

If you're looking for a catalog of algorithms along with explanations, you want a different book, but if you want to know how to analyze that bizarre code (which Fred in the next cubicle wrote) and prove that it works well (or doesn't) then this is an excellent choice.

The book is aimed at advanced undergrads/graduate students and assumes a certain amount of mathematical sophistication - i.e. calculus, discrete math, probability, etc.

On the spectrum from "Mathematical Techniques" through "Analysis of Algorithms" and ending up with "Catalog of Algorithms", I would start with Graham, Knuth and Patashnik "Concrete Mathematics", travel through this book, on to Knuth "The Art of Computer Programming", then to Cormen, Leiserson and Rivest, and finally end up with either Sedgewick's "Algorithms" or Skeina's "Algorithm Design Manual".

This is a well written book, code is easy to download, and a number of topics. All in all though, the writing is clear and easily understood so it's well worth the money...

I am a Java web/search programmer who wanted to "get into" text mining. I found this book an excellent resource for this. Text Mining is a field in which active research is still going on, and other Text Mining books I have looked at reflect this - the authors expect you to have a certain degree of mathematical background to understand what they are saying. This book explains briefly the math behind each of the approaches, but it focuses more on the algorithms that result from the math, so it is easier to read.

Of course, a side effect of this is that the approaches described are not necessarily the state of the art for solving any given problem, but once you get the basic approach to solving a problem, it is relatively easy to find and understand the documentation on the web for the more advanced approaches, since you now know what you are looking for and how it differs from your basic solution.

The book does have a (fairly long) chapter where it covers the math background necessary to get started with Text Mining. If you understand the stuff in there, you will actually be able to think up solutions to text mining problems that are unique to your own situation.

The algorithms in the book are in pseudo-code, but the book comes with a CD (or download from the author's sourceforge project textmine.sf.net) where you can see working Perl code.

Overall, I think this is one of the most useful books that I have purchased in a while. It should appeal most to programmer types who have programmed in their language(s) of choice for a while in areas other than text mining, wants to get into text mining, and doesn't want to spend a lot of time relearning high school and college math before starting off.

Text mining is one of the most exciting subjects of the web, and too few books are dealing with it. This one is one of them, and it gives quite a few examples of text mining applications, like spam filters or search engine ranking algorithms. The style is easy to follow, and the concepts easy to understand given some maths background.

However, I expected more details, and a richer content overall, thus the four stars. This is still a good book.

Software developers learn how to mine information on the Web and turn it into valuable data; but developers need to understand how data mining works. For a programmer's application-oriented review, Text Mining Application Programming is the item of choice: it reviews text data, how it's found, and how search engines locate and gather it. Next, it teaches how to build spiders to crawl the Web, how to use the information, and how to monitoring it. Perl developers will find its Perl-based code useful, but it's not necessary to know Perl to run the software herein. An excellent guide to mining the Net.

There is an old expression that half of knowing anything is knowing where to find it. And there is little more frustrating to be looking at 'My Computer' trying to find what you know you have stored in a file somewhere. Well, perhaps just as frustrating is to go to one of the search engines and try to find something that you know is there but just don't know the proper words to find it.

In this book Dr. Konchady talks about how to go find data that is in text form on your system, on your network or out on the web somewhere. It talks about search engines, but also about other techniques that can be used only by programming.

The CD that comes with the book contains several Perl software snippets that help to find named entities, parts of speech, phrases and gives a summary of text documents. This area includes developing web crawlers that can be adapted by individual users to go out and find specialized information. It further contains an Open Source software package called Text Mine that is designed for mining operations. In addition it has utilities to build and enhance Text Mine and utilities to build and manage MySQL database tables. This is an excellent book on everything from the basic hints and types through some of the mathematics that underlies text mining.

His section on the nature of an English language Question and Answer system is the best I've ever seen.

serves as a valuable tool regarding my project on AN

This is an excellent book for the signal processing community as the stress is mainly on algorithms and implementation. A reseacher who wants to work in this field without much background in acoustics, finds this book very useful and it enables him to get to know how he can apply his adaptive signal processing skills to active noise control. This book provides in a simple way the active noise control field and its associated problems. As the book provides only required amount of acoustical details and explains the filtered LMS algorithm very clearly unlike other books, for a beginer it is a very good book. I didn't know any thing aboout ANC when I started, but to day I am able to contribute even to international journals and conferences. Further I have under taken projects at national level from government agencies to develop ANC systems. I feel this book is really well written and it makes the reader keen to know about the subject and provides him high level of confidence. I sincerely recommend this book for any person who is new to this field and has signal processing background. It is a very very very excellent book.

This is an excellent book for persons with signal processing background. The book provides only minimum information about acoustics for a signal processing person and does not confuse with too much of details. In this way, the book makes to reader comfortable. Also many aspects of signal processing which can improve the performance of an active noise control (ANC)system are explained and hence the reader feels more confident that he too can work in this field. This is very much essential as the adaptive algorithms play a crucial role in the ANC implementation. The FXLMS algorithm and its problems are well described. To start with I did not know any thing about ANC, but this book has helped me to get good understanding about it. Presnently, I am able to do research contributions to international journal and to conferences. Further, I have taken up projects at national level in ANC. I feel this book has presented the subject in a simple way retaining all the intricate details. This background enables a reseacher even to follow new developments taking place in this filed. This is a very very useful and excellent book.

This excellent text is written for advanced study and practicing engineers who need to design controllers for active noise control systems. The emphasis is on the algorithms that are usually implemented in a Digital Signal Processor. The book's treatment of acoustics, sensors, and actuators is not as in-depth as texts by Fuller or Nelson. Included in the book is C and assembly code for the most popular adaptive control techniques, but beware of bugs and patent issues. One of the algorithms covered in detail is the Filtered-X Least Mean Squares technique that one of the Authors (Morgan) help to make popular in the community.

The book shouldn't be called Used, its was Crisp as New, and exactly what you wanna expect at the start of a new class, having a colourful mak free book in your hands.

The coverage of C++ and data structures looks pretty good. There are lots of programming examples, and the book is written very well. I'm recommending it for our 2nd year course in data structures and C++. Our students know Java, but not C++, so it's been a challenge finding a data structures book that packages a semi-introductory version of C++ with a standard course in data structures. This book appears to be the best suited out of about 5-10 books that I've reviewed for this course.

I actually feel that this book is a mixed bag. On one hand, the concepts are intuitively presented and are easy to understand. On the other hand, the book doesn't delve too much into technical details, which may or may not be a godsend to various students. Personally, I'd rather use the Drozdek Data Structures text, since it goes into much more detail into analysis and logic behind choosing various data structures and algorithms in order to implement an ADT.

Anyway, it's still a great textbook for an introductory course in data structures. Just be sure to get another textbook on the same material down the road if you want to get a more detailed understanding of the concepts presented.

I am teaching the second programming / first data structure course in the department of electrical and computer engineering. I have used the first edition of this book several times, and as of fall of 2004 I am into the third of semester of using this second edition as a mandatory text.

This book is very good for students who already know how to program in C, C++ or Java. The first C or C++ course does not have to cover introduction to OOP though. My students learn C part of C++ in the first programming course. This book covers object oriented programming part of C++, and introduces/reintroduces pointers, file IO with streams, and C++ strings (good for former Java programmers). Then it follows into data structures. It starts with its own definitions of dynamic array that grows, and a simple linked list as basic data containers. Then it focuses on organizing access to data with stack and queue, and then migrates to the standard template library (STL). Everything is kept on the undergraduate student level. All other STL books I know assume that you are already an expert in programming or at lest for students after two programming courses, and are too difficult for average non-CS students.

I originally rated the first edition with four-stars only because it introduced pointers very late, out of the proper sequence and added the fifth star for the unique blend of introduction to OOP C++ and data structures, and STL. However, this edition is free from this inconvenience and it also makes C++ and data structures course accessible to former Java programmers. It gets true five stars from me this time.

Just bought the book and it has been useful already. If you are serious enough about computer science to want to know what is in the professional literature this is full of wonderful summaries.

This book is an incredible resource for all people interested in software engineering and AI. I've used numerous ideas in from this book in current research projects, and I'm sure that my copy will become well worn with time! -Ben Peterson, Computer Science student

This book is a compilation of texts on different, very interesting, fields on theory of complexity and theory of algorithms. It is very usefull for all that are interesting in the field. Contains mary recent results and concepts.

Knuth's Art of Computer Programming summarized the state-of-the-art in research into algorithms in the seventies and set bar formidably high both in breadth and depth of presentation. Atallah's Handbook is one of the better attempts to survery the present, much wider scope of research in the field, even if it's lacking in Knuth's profundity. It most certainly makes an interesting read if you have the time it takes. If you enjoyed reading Knuth, you will enjoy browsing through Atallah as well.

I have been using this book as a second reference in my Algorithm
Engineering class during the whole semester. I found it extremely useful for its nice structure, content and diversity of subjects treated, especially the ones in computational geometry such as Geometric Sweeping and Voronoi diagrams, for instance. I believe this book should be useful to any student taking algorithms class for its structureness, clearness, and completeness.

This is a great book overall, but I give it 4 stars as it lacks the mathematical explanations that I personally was looking for. I am graduate student in Computer Science and a E-Commerce Consultant by profession. This book is more detailed than the Sedweick (I can't spell his name) in the sense that it has some more of a mathematical approach. It lacks the level of explanation that the Sedweick book provided. It has some math, but overlooks some steps thus targeting someone with a pretty solid math background, not someone with sophomore level undergraduate math background.

Overall.. if you're a student taking an algorithms or advanced algorithms class (especially a graduate class), you might want to invest in this book.

I have studied both undergrad and grad algorithm courses from this book at KFUPM. For a beginner, the author provides a moderate level of mathematical analysis which helps in building a solid foundation, but avoids minor details that may obscure the overall grasp of the subject. The Exercise sets at the end of each chapter vary from easy to challenging....

The book represents a well written, consistent and easy to follow view on the area of algorithm analysis. It gives an excellent overview of various mathematical and computer science areas, including but not limited to combinatorial geometry, NP-problems, complexity theory, graph theory, algorithm analysis, dynamic programming and even computational geometry.

Most of the chapters are intended for a senior level undergraduate and graduate student, but some (such as part 4 devoted to complexity problems) are more suitable for "mature" audience and require some preliminary knowledge in the area.

I found chapters on sorting, data structures, recursion and functional programming well written and structured, and examples to be practical as well as informative.

Sections on amortized analysis, randomized algorithms, approximation algorithms and iteration improvement deal with current directions in the algorithmic research and provide an excellent overview of the "state-of-the-art" in these areas. I also enjoyed reading through the section on greedy algorithms (shortest path and minimum spanning tree problems).

Section on computational complexity and analysis of the relationship between complexity classes seems to be a bit complicated, those who are interested in this area should probably do some preliminary reading.

The last section on computational geometry (my area of expertise) and applications of Voronoi diagrams could be extended, but even in the current state it givs a pretty good idea of what computational geometry is all about.

Overall, I give to this book a "5 star" review and recommend it for anyone who is seriously interested in learning exactly how algorithm design and analysis work. I thoroughly enjoyed reading this book and can only wish that author would write more books like that in the future!

The books are very detailed and take a lot of analysis... they are not written in a current Object Oriented Language... that was a disappointment but otherwise it is very good... just uses old "spaghetti code"

This fascicle can perhaps best be read as a sequel to Knuth's Volume 3, on sorting and searching, where he discusses trees. The fascicle extends that into how does one generate every tree. Of the four fascicles thus published, this might be the skimpiest in terms of current mathematical knowledge. Though to a practising programmer, trees are a vital construct and the book could well have germane analysis. And, as with his other books in this series, there is a tough set problems that can be just as instructive and interesting as the text.

Still, to perhaps compensate for the thin length, the book contains a distinctive section on the history of combinatorial generation. Knuth delves into this subject while giving a deeper treatment of the maths than one would likely encounter in a popular text directed at a general audience. He cites the I Ching, as well as ancient Indian and Arab manuscripts. The I Ching is notable as it is still in print and likely to be familiar to many.

With the publication of this fascicle, the collective set of four would make a respectable book in its own right. However, Knuth is scarcely done yet. We can expect more fascicles, and soon, one might hope. And eventually, a hardcover.

The fourth volume in the classic ART OF COMPUTER PROGRAMMING: GENERATING ALL TREES: HISTORY OF COMBINATORIAL GENERATION add to and expands upon a multi-volume work on the analysis of algorithms in classical programming, updating sections of the set using a series of small fascicle books. This covers the generatio of all trees, a topic covered in the first three volumes of ART OF COMPUTER PROGRAMMING, and provides over a hundred new exercises to programmers.

I've known about The Art of Computer Programming volumes by Donald E. Knuth for some time, but I've always avoided reviewing them for fear of not being able to do them justice. But after being contacted specifically by the publisher asking if I was interested in the latest - The Art of Computer Programming, Volume 4, Fascicle 4 : Generating All Trees--History of Combinatorial Generation - I decided to give it a try. For the right audience, this is really good stuff. But I can tell you that I'm not it...

Content:
Chapter 7 - Combinatorial Searching: 7.2 - Generating All Possibilities; 7.2.1 - Generating Basic Combinatorial Patterns; 7.2.1.1 - Generating all n-tuples; 7.2.1.2 - Generating all permutations; 7.2.1.3 - Generating all combinations; 7.2.1.4 - Generating all partitions; 7.2.1.5 - Generating all set partitions; 7.2.1.6 - Generating all trees; 7.2.1.7 - History and further references; Answers to Exercises; Index and Glossary

Don't refresh your browser thinking the Content section didn't load properly. There's just chapter 7... For those who don't understand the "fascicle" concept (like I didn't before getting this volume), it's a small book (120 pages) of material that either updates writings in previous volumes or a "preview" of material that will eventually be rolled into a single volume (in this case, volume 4). Knuth has a lot of information he wants to convey, and by using fascicles, the public can get a steady flow of information and help shape the continuing evolution of the series. Interesting concept, and one I can appreciate. Another review stated that this was probably one of the "skimpiest" volumes in terms of mathematical knowledge. If true, then I fear what will await me with future installments. To get the most of out Knuth's work, you really do need to be well-grounded in computer science and mathematical theory. Every page is populated with numerous formulas to prove the subject matter, and I'll admit to being completely lost in most of it. That doesn't mean the book isn't good. It *is* excellent work, but I'm definitely not the target audience. I don't come from a formal computer science and mathematics background, so I'd have to really slog through everything from page 1 with supporting texts in order to fully benefit from it.

It wasn't a total loss for me, though... I enjoyed the History and Further References chapter, where he shows the tree theory and how it affected such things as literature and culture through the ages. Whether the ancient Chinese had all this in mind when developing the I Ching is open to debate, but the theory and underpinnings of trees is definitely there. And for those readers who really want to work through and apply the material, there are exercises galore at the end (with answers graciously provided for those who get stuck). You could likely set up a college level course based on this (and associated) book, and it would be foundational to a computer science degree.

So, for the right audience, this is the type of book that will allow for weeks of thought and learning. But if you're more like me, someone who deals more with business systems and development (without a comp sci degree to back it up), you'll likely miss most of the value here.