Product Description

To even try to keep pace with the rapid evolution of game development, you need a strong foundation in core programming techniques-not a hefty volume on one narrow topic or one that devotes itself to API-specific implementations. Finally, there's a guide that delivers! As a professor at the Spanish university that offered that country's first master's degree in video game creation, author Daniel Sanchez-Crespo recognizes that there's a core programming curriculum every game designer should be well versed in-and he's outlined it in these pages! By focusing on time-tested coding techniques-and providing code samples that use C++, and the OpenGL and DirectX APIs-Daniel has produced a guide whose shelf life will extend long beyond the latest industry trend. Code design, data structures, design patterns, AI, scripting engines, 3D pipelines, texture mapping, and more: They're all covered here-in clear, coherent fashion and with a focus on the essentials that will have you referring back to this volume for years to come.

Customer Reviews (17)

Reads like a textbook
This book bored me to tears. It reads like a text book, theres rarely an example. I don't get any explanation of what tools to use, how to set them up, or anything that i can actually work on while reading the book.

For a 'programming book' i felt this fell way short.

I did learn a lot of concepts by reading it, i just didn't learn any real C++ programming techniques, because they didn't give me enough background to get started in any compilers.

Very informative and concise
The content in the book definetly adheres to the title of the book.It covers major design patterns used in the current video game industry, and always keeping in mind to stick with the logic behind many game aspects, and not just merely giving out code.Tho, not meant for completely new video game programmer wannabes, it does anticipate and appease the needs of one who would want to start their own video game project.Before going on and buying this book, the reader should be very experienced with key programming concepts such data structures, ai, and programming in general.Furthermore, readers should have already created simple two 2d games such as tetris, a 2d scroller, and other related game material.For instance, many topics in the book are better understood by someone that has some game programming experience, because they can actually relate to the books content and understand it.In conclusion, it deserves 4 stars simply because of the fact that it lives up to its name and the target audience!

For beginners only
I find it telling that the author's bio does not mention any games that he has worked on, because it quickly becomes apparent when reading it that this is *not* the advice of a seasoned developer, and I doubt that he has worked on anything more than very small demos.The book does cover a broad range of techniques and algorithms that are applicable to game programming, but it seems that the author's knowledge of these techniques is of an academic nature - gleaned from reading other books or newsgroups and a little dabbling in his spare time, not from professional game development.As such, it provides an introduction to quite a lot of topics, but as soon as it comes to adding more detail on implementation or practical advice, he suddenly becomes very vague and occasionally just plain wrong.Furthermore, his programming style is very academic (smells of unix) - not of the standard expected of a professional programmer.

The book may serve as a good warm-up for a student wishing to enter the industry, but for anybody with a year or two under their belt it is unlikely that they will find anything here to improve their skill set.This does not necessarily make it a bad book, as there are plenty of people out there who want to get into the industry and don't know where to start, and more in-depth books would probably create information overload.However, the book would have got a higher score if it had included the word "introduction" in the title somewhere.As it is pitched, as a reference book for the industry, it is a definite disappointment.

Disappointing. A lot of info, but sloppily done
This is an ambitious and expensive book. In my opinion it isn't really worth the cost. I have two major criticisms: first, there is no CD with code samples, and no color plates for showing off graphics. Second, it is *very* poorly edited, and the code formatting is so bad as to be almost unreadable.
For example, on page 576 on reducing texture memory requirements the author talks about how using RGB4 is generally okay if you don't have fine color gradients. This is correct. He then refers to an unnamed figure (which we find on the next page) but swaps the left and right side (presumably) defeating his point. He then later refers to the figure, by number, but with completely incorrect content. The actual picture referred to was apparently removed, and the wrong one got its number. This is not an isolated incident. Page 329 has a nasty (yet typical for integer divides) off-by-one error.
Further, I find he often uses pseudo-code where you would want details, and real code where you would want pseudo-code. And the coding style used is also poor, especially when one thinks it is meant to be an example to new programmers. Often #define's are written exactly like normal variables and are used when enums would be much better, upper case and lower case are regularly switched when referring to the same variable, long, unreadable, all lowercase variable names are used, constants are not brought out of loops, braces are not matched up, erratic use of whitespace, etc.
I also found discussion often sadly lacking. The book is admittedly already large, but much could be cut out that isn't interesting or germane (e.g. pages of badly formatted code, or mixing force-feedback effects for DirectX which belongs in a DirectX book). For example, in discussing A* searching no mention is made of using pessimistic heuristics, which in practice can dramatically improve performance. In a very brief section of Design Patterns, no discussion is made about why the author thinks its better to subclass strategies rather than use function pointers.
Some statements are just wrong: "As anyone familiar with algorithm theory knows, sorting a list of N numbers needs at most N log N comparisons, and no algorithm can perform better than that (in a worst case scenario)." Well, in fact, if you can meet certain criteria, you *can* sort in O(N) time (even in the worst case), and many "standard" algorithms require N*N comparisons in the worst case.
There are some good points. The history of games was quite interesting, as was the review of tiling, sprite, and palette techniques. And, if you're a complete beginner to programming, there's a fair bit of useful information, and I'd give the book 3 stars instead of two. Even experienced game programmers will probably learn something, or at least be pushed in that direction. The explanation of BSPs was quite good, for example.

All in all, disappointing. For reference, I've programmed the PlayStation (one) for Electronic Arts, and more recently done gaming stuff for mobile phones, and have a background and interest in gaming, 3D graphics, and AI.

good for general information
I have read about half of this book so far. I was very excited about this book while reading it because it does contain a lot of useful general information. However, if you are looking for actual code examples...this book falls short.

I am writing my own game engine right now and I went to the book to use an algorithm it had listed...except the algorithm doesn't actually work! i tried to debug the algorithm for hours before giving up and writing my own. (Which was a good exercise in itself) Once again I turned to the book for an algorithm it listed, but the explaination of it was so bad I decided to write that one myself too.

So...if you are a programmer already this book will be useful to you because the code snippets provided are less important that overall concepts which is why i bought it in the first place. But if you are a beginner programmer looking to learn how to code, I wouldn't recommend this book to you. ... Read more

Product Description
Since the initial work on constrained clustering, there have been numerous advances in methods, applications, and our understanding of the theoretical properties of constraints and constrained clustering algorithms. Bringing these developments together, Constrained Clustering: Advances in Algorithms, Theory, and Applications presents an extensive collection of the latest innovations in clustering data analysis methods that use background knowledge encoded as constraints.

Algorithms

The first five chapters of this volume investigate advances in the use of instance-level, pairwise constraints for partitional and hierarchical clustering. The book then explores other types of constraints for clustering, including cluster size balancing, minimum cluster size,and cluster-level relational constraints.

Theory

It also describes variations of the traditional clustering under constraints problem as well as approximation algorithms with helpful performance guarantees.

Applications

The book ends by applying clustering with constraints to relational data, privacy-preserving data publishing, and video surveillance data. It discusses an interactive visual clustering approach, a distance metric learning approach, existential constraints, and automatically generated constraints.

With contributions from industrial researchers and leading academic experts who pioneered the field, this volume delivers thorough coverage of the capabilities and limitations of constrained clustering methods as well as introduces new types of constraints and clustering algorithms. ... Read more

Product Description

Amazon.com Review
This book's introduction features a humorous story of a manwith a line of people behind him, who explains to his boss, "Ican't find an efficient algorithm, but neither can all these famouspeople." This man illustrates an important quality of a class ofproblems, namely, the NP-complete problems: if you can prove that aproblem is in this class, then it has no known polynomial-timesolution that is guaranteed to work in general. This quality impliesthat the problem is difficult to deal with in practice.

The focusof this book is to teach the reader how to identify, deal with, andunderstand the essence of NP-complete problems; Computers andIntractability does all of those things effectively. In a readableyet mathematically rigorous manner, the book covers topics such as howto prove that a given problem is NP-complete and how to cope withNP-complete problems. (There is even a chapter on advanced topics,with numerous references.) Computers and Intractability alsocontains a list of more than 300 problems--most of which are known tobe NP-complete--with comments and references. ... Read more

Customer Reviews (13)

Definitely a classic but not good for beginners
I have to say that this is a true classic.It gives a very nice treatment of what is NP-completeness in a fashion that really defends the topic well.It gives nice illustrations to show different situations and how to deal with it.But after the first couple of chapters it does get a little out there with the proofs it does.It is still approachable, but it assumes that the reader is already familiar with the basics of combinatorial complexity, especially in reductions.I would only recommend this book to readers who has gone through such books as Introduction to Algorithms by Cormen et al. or Combinatorial Complexity by Papadimitriou and Steiglitz.Those two books are more for beginners and this book should be one to help anyone interested in NP-complete problems to get more practice and depth understanding.Overall a great book for anyone interested in the topic.The grand challenge is to reduce everything to at least something within the 150 problems listed on your own.

comprehensive book for NP-completeness
The book is excellent in explaining NP-completeness problem. Take it as a reference if you would like to do research in this field.

Published in 1979 and still the best
This is a rare example of a textbook where the authors actually go to the trouble of considering the fact that the intended reader is a non-expert. Published in 1979 and still the best.

Arrived in time, good condition
The book arrived in time, in good condition, and adequate packing.

A Beautiful Book on a Beautiful Subject
This is among the most eloquently written books that I have ever read in my life.Highly recommended. ... Read more

Product Description
The primary goal of this book is unifying and making more widely accessible the vibrant stream of research - spanning more than two decades - on the theory of semi-feasible algorithms. In doing so it demonstrates the richness inherent in central notions of complexity: running time, nonuniform complexity, lowness, and NP-hardness. The book requires neither great mathematical maturity nor an extensive background in computational complexity theory or in computer science. Another aim of this book is to lay out a path along which the reader can quickly reach the frontiers of current research, and meet and engage the many exciting open problems in this area. ... Read more

Customer Reviews (1)

lane hemaspaandra is my hero
omg lane hemaspaandra is brilliant he is like so totally da theory man buy this book now goodbye. ... Read more

Product Description
Covers fundamental data structures and algorithms for sorting, searching, and related applications. Includes expanded coverage of arrays, linked lists, strings, trees, and other basic data structures. Contains many examples. Paper. DLC: C (Computer program language) ... Read more

Customer Reviews (20)

A Classic on Algorithms...
...that is as relevant today as when it was first written.

As a computer scientist for 20 years, few books have had as long lasting an impact as this book. What has always amazed me is that once you've worked your way through an algorithm, and Sedgewick's explanation, you remember it. For me, it was, and still is, a foundation of computer science and as ready a reference today.

Really liked the writing style, Sedgewick does a good job of keeping the explanation human-friendly. Face it, it's a book on algorithms, not quite a summer reading beach book. :-)

All told, I put this book up with the Knuth series...btw, Sedgewick was a student of Knuth's.

Enjoy, and hope it helps out as it did me.

Great book a must have
This is one of the best book that I have ever read. The writer explained data stucture in a very good detail.
However, this is NOT a book for those beginers, writer assumed that readers must have some strong background in both C programming and math. As many C code functions are left out.
There is a clear difference between IT and computer science, if you just make web pages, click mouse in windows, know a little bit about programming, you will find this is a book hard to read and follow. On the other hand if you are computer scientist, digging underground understanding of lists, tree, pattern matching. This book is, undoubtedly the one to go.

SedgeWork
If you purchase this book as I did then be prepared to expend quite a lot of energy to derive any useful learning from this text.I am in full agreement with many of the other reviewers here as to the quality of this book.And I am not just referring to the numerous glaring typos and off-by-one errors but what seems to be a fundamental inability of this author to be able to explain himself in a clear, coherent manner.I do not expect the quality or caliber of say a "Richard Stevens", on every technical publication but this work is below par from what one would expect from a "professor".I have read many technical books over the years, on protocols, programming languages and data structures and algorithms.Reading through the text, and for books like this, compiling and running the examples, is par for the course.You learn by doing not just by reading alone.But a balance should be maintained.

It does have some redeeming qualities.It does cover a fair amount of material about algorithms.It does offer insight not available elsewhere (at least not in book form).But this is not a reference work you can look at while coding at work and pull some algorithm out of that you forget the details about.

Some say this work is densely populated.I believe this to be a misunderstanding.This book is terse in some respects and filled with circumlocutions in other places.An example of a dense, and yet clear and concise technical book would be "The Annotated C++ Reference Manual".

The author leaves out so many fundamental and subtle points regarding the subject matter that no student could hope to come away with a thorough understanding -- unless of course you perform the following:

type_the_examples();

for (i = 0; i < MaxTimesBeforeBecomingFrustrated; i++)
{
study_section_of_text();

for(j = 0; j < RunTimesBeforeYouForgetWhatYouWereStudying; j++)
{
run_code();
examine_output();
analyze_program_source();
fix_errors_and_assumptions_from_text();
compile();
}
}


Assumptions are made with the code examples that require careful attention on the readers part or you WILL end up with Segmentation faults.

The book does provide the material needed to form a basis in exploring ideas in the covered algorithms.But I found that I had to read through the code examples and run the examples to be able to meaningfully interpret what the text was stating.The examples usually form a basis for reinforcing the reader's understanding of the text but with this book this paradigm is inverted; without the code examples it would be futile.

The author mentions, justifiably so, that changing the input data would change the runtime characteristics of some particular program.Well, try this with numerous examples in the text and you will demonstrate first hand not how the performance might change but just how fragile the code is as witnessed by your accompanying seg fault.

In the end, you can learn from this text but it requires a great deal of work, and quite a lot of debugging; more so that what is normally necessary.Learning any technical matter is work for the most part but learning from this text is, in my experience not enjoyable work.The above issues end up distracting the reader from being able to focus on learning the algorithms which is supposedly the reason you bought the book in the first place.My fear is that any young reader (all but the most ardent), who picks up this book as his/her first book on Algorithms will be turned off from Computer Science for good.We have enough of those books already.

I'm fed up with these books
I bought these two book for one reason: to get help implementing algorithms. Since there is lot of code in these books, I thought this would be a good pick. I was wrong. The author is consistently leaving out details vital to understanding the code. He also makes a big deal about abstract data types. This is gloriously of the case. If the readers are supposed to understand the code, transperency would be a more intelligent goal for the author. There are no comments in the code what so ever (yes, this is actually true, not even in the on-line code). The on-line code to this book is a total mess. You would be able to implement all the algorithms from scratch in less time than it would take you to try an piece together the code the author has left for you. The pity is that there are very few other algorithm books that have real code.
Instead of moving on to writing C++ and Java editions of this book, the author should fix the problems with this book and the part 5 book.
Demand a new edition from the author and don't by this one unless you can avoid it. You deserve better.

why someone give the book 5 star?
this is the first algorithms book i read, this is last robert sedgewick book i read. ... Read more

Product Description
Information retrieval is a sub-field of computer science that deals with theautomated storage and retrieval of documents. Providing the latest informationretrieval techniques, this guide discusses Information Retrieval datastructures and algorithms, including implementations in C. Aimed at softwareengineers building systems with book processing components, it provides adescriptive and evaluative explanation of storage and retrieval systems, filestructures, term and query operations, document operations and hardware.Contains techniques for handling inverted files, signature files, and fileorganizations for optical disks. Discusses such operations as lexical analysisand stoplists, stemming algorithms, thesaurus construction, and relevancefeedback and other query modification techniques.Provides information onBoolean operations, hashing algorithms, ranking algorithms and clusteringalgorithms. In addition to being of interest to software engineeringprofessionals, this book will be useful to information science and libraryscience professionals who are interested in text retrieval technology. ... Read more

Customer Reviews (4)

Covers Basics with Varying Depth and Quality
Rather than a coherent textbook about information retrieval, this book contains 18 papers by individual authors which vary wildly in depth, quality and relevance today.The basic issues are covered each with their own chapters: inverted files, vector comparison techniques, stoplists, stemming, tehsauri, string searching, relevance feedback, boolean operations, ranking, clustering and hashing.

The introduction covers hashing and automata for string matching in detail, but doesn't mention vector-based techniques other than Hamming distance (!) and in one paragraph provides the only mention of edit distance (aka Levenstein distance) in the book.The chapter on PAT trees and the one on optical disks seem out of place due to their depth and obscurity.On the other hand, there's no mention of caching anywhere.The chapter on lexical analysis and stoplists by Fox has a nice introduction, but then devolves into page after page of C code.Ditto for Frakes' chapter on stemming -- good introduction, but we didn't need ten pages of code.Same for the thesaurus chapter -- a few pages of introduction, and then 40+ pages of code for some kind of hierarchical clustering.Baeza-Yates' chapter on string searching covers Knuth-Morris-Pratt and Boyer-Moore briefly and even contains some interesting empirical data, but again, we didn't really need the C code.Harman's chapter on relevance feedback (query modification) stands out as being entirely sensible, high level and informative, but is a decade behind the times.The chapter on boolean operations provides a few pages of info and then mysteriously spends 10 pages on bit vector code and then another handful on hashing.Then the following chapter on hashing has 40 pages of C code for perfect hashing!Harman's later chapter on ranking algorithms is a useful overview of scoring (though very high level).Rasmussen's chapter on clustering is also thoughtful, but rather non-standard -- you don't even get k-means, everyone's favorite clustering algorithm, and it also recaps the definitions of many of the other chapters.

Unfortunately, you don't get any higher-order graph analysis techniques that power web search engines like Google.You won't get any kind of help for load balancing servers or databases, which is critical. You also don't get any dimensionality reducing and smoothing techniques like latent semantic analysis or principal components analysis.There's also no analysis from a users' perspective on usability and the different kinds of tasks that peopel might be using information retrieval for.And of course, there's no discussion of natural language understanding techniques or crosslingual or multilingual retrieval techniques.Finally, it's all text based and you won't get any information on retrieving audio or images.

If you're serious about information retrieval, this book lacks the depth and recency to leave you feeling like an expert.The statistical language processing book by Manning and Schuetze contains an excellent introduction to information retrieval algorithms, as well as reams of background on statistical language processing you'll want to understand before getting into information retrieval.For more details on information retrieval itself, check out the collection of primary source papers edited by Karen Sparck-Jones: Readings in Information Retrieval.

Useful reference book
I bought this book while working on some informaitno retrieval related project, and it turned out as a useful reference for explaining terminology, suggesting efficient data structures, and offering good references for further reading.

However, the book turned out yet more useful to me as, during my M.A. studies (in CS) I had to write a work on "Suffix Trees" and "Suffix Arrays" and I found that Gonnet, Baeza-Yates and Snider describe equivalent ideas they call "PAT trees" and "PAT arrays".

I found this book useful too for working on computational linguistics related projects as well.

In short - I like keeping this book always in reach, as a reference, though, I found this book not so friendly as an introduction book to the subject ("Managing Gigabytes", might turn out to be a more welcomming).

Good coverage and treatment of algorithms for I.R.
I adopted this book as the primary textbook for my course on information retrieval. It covers a substantial part of core topics in IR: models of information retrieval system (boolean and best-match systems);implementations (inverted files, tries, signature files, hashing), indexingand retrieval algorithms (lexical analysis, stemming, ranking, relevancefeedback, boolean operations) and somewhat more advanced topics likeclustering and automatic thesaurus construction.These topics are dealtwith varying level of detail: for some of them there are also C codeexamples that are rather useful to students; other topics are less welldetailed (eg. relevance feedback and probabilistic models).These topicsare dealt with sufficient clarity and reasonable conciseness. Someshortcomings are: (i) the weak treatment of the probabilistic models (Iwould have liked a deeper analysis of the underlying principles and howthey lead to certain kinds of systems). Consequences of some techniques arediscussed with insufficient depth. (ii) In my view too much attention isdevoted to low-level string processing, like what is done in chapter 10,centered on string searching algorithms (not relevant to the main topic ofthe book). (iii) Other important topics have not been dealt at all,unfortunately. These include almost everything that goes under the topic ofuser-centered information retrieval and user interfaces. Another missingtopic is "passage retrieval".

good tips on how to get the right bits of knowledge to user
Although this is more of a hardcore software book, the techniques and issues presented are transferable to the general problem of knowledge management.In particular, the various software tricks for how to handle very large databases provide useful ideas on how to get the right bits of knowledge to the user. ... Read more

Product Description
Algorithms for VLSI Physical Design Automation, ThirdEdition covers all aspects of physical design. The book is a corereference for graduate students and CAD professionals. For students,concepts and algorithms are presented in an intuitive manner. For CADprofessionals, the material presents a balance of theory and practice.An extensive bibliography is provided which is useful for findingadvanced material on a topic. At the end of each chapter, exercisesare provided, which range in complexity from simple to research level.Algorithms for VLSI Physical Design Automation, Third Editionprovides a comprehensive background in the principles and algorithmsof VLSI physical design. The goal of this book is to serve as a basisfor the development of introductory-level graduate courses in VLSIphysical design automation. It provides self-contained material forteaching and learning algorithms of physical design. All algorithmswhich are considered basic have been included, and are presented in anintuitive manner. Yet, at the same time, enough detail is provided sothat readers can actually implement the algorithms given in the textand use them. The first three chapters provide the background material, while thefocus of each chapter of the rest of the book is on each phase of thephysical design cycle. In addition, newer topics such as physicaldesign automation of FPGAs and MCMs have been included. The basic purpose of the third edition is to investigate the newchallenges presented by interconnect and process innovations. In 1995when the second edition of this book was prepared, a six-layer processand 15 million transistor microprocessors were in advanced stages ofdesign. In 1998, six metal process and 20 million transistor designsare in production. Two new chapters have been added and new materialhas been included in almost allother chapters. A new chapter onprocess innovation and its impact on physical design has been added.Another focus of the third edition is to promote use of the Internetas a resource, so wherever possible URLs have been provided forfurther investigation. Algorithms for VLSI Physical Design Automation, Third Edition isan important core reference work for professionals as well as anadvanced level textbook for students. ... Read more

Customer Reviews (4)

This book will confuse you
This book is good at introducing basic concepts, if this is what
you want to know. But it is really bad to introduce algorithm.
It simply confuse you. Many time I don't know what the author
is talking about and have to find the original paper, which is
much clear.

Algorithms for Vlsi Physical Design Automation
I read the Chapter on clock routing and found that the
author did not do a good job on explaining about DME
algorithm. I got more confused after reading it. So,
I went to the library and checked the references
which gave me clear understanding. Usually, a book
shoud give a reader with a very clear example about
the algorithm it presents. It's was not the case for
the DME algorithm.

Algorithms for Vlsi Physical Design Automation
I found this book very helpful in gaining a deeper understanding of what the tools I use are doing. Also, the terminology that is used and explained allows me to easier communication with the CAD developers. I found the information relating to clock skew and jitter of particular value to my daily work.

Suitable for CS people
Very comprehensive in VLSI physical design automation. People who major in Computer Science and want to study in VLSI is suitable to buy this book. Also people who want to develop EDA tools can buy the book. ... Read more

Product Description

In this text, readers are able to look at specific problems and see how careful implementations can reduce the time constraint for large amounts of data from several years to less than a second. This new edition contains all the enhancements of the new Java 5.0 code including detailed examples and an implementation of a large subset of the Java 5.0 Collections API. This text is for readers who want to learn good programming and algorithm analysis skills simultaneously so that they can develop such programs with the maximum amount of efficiency. Readers should have some knowledge of intermediate programming, including topics as object-based programming and recursion, and some background in discrete math.

Customer Reviews (19)

An awesome advanced data structures & algorithms book
This book is quite advanced as many others have written in their reviews. Maybe it should have had a "pre-requisites" section, telling what background the author expects from the reader. BUT with that said, I love this book and could not put it down from the time I started reading it.

Weiss has driven the points across very well. Right from page 1 the book is quite exciting to read. Weiss stresses the importance of recursion and shows many good (and a bad) uses of recursion. Chapter 2 illustrates bad and good algorithms with elegant examples - all the algorithms and their computational complexities are explained in detail very well in Sec. 2.4.3. I could not wait to get to the O(N) algorithm, and then there is the surprise - it is so simple, what the heck am I missing? And then you realize you are not dumb and the short program does involve some serious intelligence behind it!

This book has really flexed my mind very well and I love reading it! I am sure I will learn a lot more as I read more from it. And I feel this book does not deserve a poor 3-point rating and does deserve more 5-point ratings by advanced readers.

book was stolen from a library??
Condition of the book is acceptable, somewhat used and marked up. No problem with delivery.BUT:

This is evidently a book from a college library, with the library name, stamp and barcode still in it, and a due date less than 2 months before I purchased this book.The RFID set off alarms when I carried the book into the library at our university here.

I checked the library's website and this book is listed as Missing. It's upsetting to find I am at the receiving end of a book that was either improperly removed from a library or stolen from the person who checked it out. I would not patronize this seller again.

Could have been better
I felt the author has a firm understanding of the concepts and truly what he wanted to convey, but this book lacked a great deal for beginners or newcomers to Java. Far too many of the examples were tough to understand and in many cases simply un-answered. This is not a book for beginners.

Not as good as I expected
It is a nice book but i expected something better. I don't know what it is but something is missing here. I like the C/C++ version of this book better for some serious learning. On the other hand this is a good opportunity to learn java programming at the same time if you haven't mastered it yet.

not a book for beginners
If you don't know Java, don't expect to be able to learn the things you need to for a class.If you learned how to do alorgithms in mathematics, it may not be enough for computer science.You probably want to get a supplemental or two if you have to get this book for class.It is quite advanced and a hard read. ... Read more

Product Description

Algorithms and Theory of Computation Handbook, Second Edition provides an up-to-date compendium of fundamental computer science topics and techniques. It also illustrates how the topics and techniques come together to deliver efficient solutions to important practical problems.

New to the Second Edition
Along with updating and revising many of the existing chapters, this second edition contains more than 20 new chapters. This edition now covers external memory, parameterized, self-stabilizing, and pricing algorithms as well as the theories of algorithmic coding, privacy and anonymity, databases, computational games, and communication networks. It also discusses computational topology, computational number theory, natural language processing, and grid computing and explores applications in intensity-modulated radiation therapy, voting, DNA research, systems biology, and financial derivatives.

This best-selling handbook continues to help computer professionals and engineers find significant information on various algorithmic topics. The expert contributors clearly define the terminology, present basic results and techniques, and offer a number of current references to the in-depth literature. They also provide a glimpse of the major research issues concerning the relevant topics.

Customer Reviews (4)

The Art of Computer Programming 40 Years Later
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.

Confirm: Excellent Resource
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.

Excellent Computer Science Resource
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 withtime! -Ben Peterson, Computer Science student

Great comiultion of texts on Comlexity and algorithms
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 andconcepts. ... Read more

Product Description
While there are dozens of books on programming algorithms, never before has there been one that uses Perl. Using the algorithmsexplained here, you'll be able to carry out traditional programmingtasks in a high-powered, efficient, easy-to-maintain manner with Perl.This guide assumes a basic understanding of Perl syntax andfunctions, but not necessarily any background in computer science.The authors clearly explain the reasons for using various classicprogramming techniques, the kind of applications that use them,and -- most important -- how to code these algorithms in Perl.Topics range in complexity from sorting and searching to statisticalalgorithms, numerical analysis, and encryption.If you are an amateur programmer, this book will fill you in on theessential algorithms needed to solve problems just like an expert. Ifyou've learned algorithms in other languages, you will be surprised at how much different (and often easier) it is to implement them in Perl.The authors include the editor of The Perl Journal and the master librarian of CPAN; all are contributors to CPAN and have archived much of the code in this book there.Amazon.com Review
Written for readers with at least some Perl programmingexperience, Mastering Algorithms in Perl delivers a solidlibrary of algorithms written in Perl for business and mathematicalcomputing. From data structures to cryptography and more advancedmathematical algorithms, this book provides a worthwhile guide toextending Perl's coding capabilities.

The best thing aboutMastering Algorithms in Perl is the scope at which it coversthe universe of algorithms while refraining from getting bogged downin academic detail. Besides basic data structures--a lynchpin of bookson algorithms--the authors provide dozens and dozens of algorithms forsorting, searching, and doing mathematical computations of allkinds. While they discuss "Big-O" notation and assume a generalfamiliarity with math, they don't overwhelm the reader. (You can evenborrow the code without needing a math degree to understand it.) Thefocus is on efficient, reusable Perl subroutines written and compiledby three Perl experts.

Standout chapters include extending Perl'salready powerful string processing abilities, game programming, andcryptography. Generally, the authors achieve a good mix of moreadvanced (and less well-known) algorithms, along with thebasics. Chances are you won't need to use all the dozen or so sortingalgorithms presented here, but the authors include them all, just incase. As a reference and tutorial, readers can pick and choose whatthey need for real-world Perl development.

There hasn't been a bookdedicated exclusively to Perl algorithms prior to the publication ofthis one. In all, Mastering Algorithms in Perl fills a usefulniche by compiling a powerful library of Perl algorithms that will beuseful for anyone who works with this programming language, whether inbusiness or academic computing. --Richard Dragan

Topicscovered: Perl data types, Big-O notation, data structures, queues,deques, linked lists, binary trees, sorting and searching algorithms,game and dynamic programming, sets and multisets, matrices and graphs,string matching and parsing, 2-D geometry, number systems,cryptography (including DES and RSA), probability, statistics, andnumerical analysis. ... Read more

Customer Reviews (17)

Enjoyable, broad-ranging coverage of algorithms
This is a very accessible introduction to data structures and algorithms in Perl. It doesn't go into a lot of theory, it isn't going to answer your computer science homework, but it does give a good feel for the various applications of algorithm research.

Plus, the code is all in Perl, which is not as unreadable as received wisdom asserts. It's certainly more accessible for the interested Perl-savvy amateur than the pseudocode in Introduction to Algorithms.

Obviously, you're going to have to move onto the likes of Cormen et al, if you're really serious about this stuff. And practically speaking, yes, most of this can be found in CPAN without you having to worry your pretty little head about the mechanics. If just getting something done is your main concern, then this is not the book for you.

Plus, it must be admitted that the level of detail varies across the chapters, and some of the explanations can be opaque, even for the simple stuff. I felt I had to work unnecessarily hard to comprehend some of the material: the discussion of the A* algorithm, some of the tree-related algorithms and the section on compression all suffered from this to varying degrees. This is the sort of book which requires concentration (plus copious scrap paper for scribbling down arrows and boxes) to get anything from.

But to complain that Perl doesn't need you to write these data structures from scratch, and it isn't a suitable language for this sort of thing anyway, is to miss the point of at least part of the book. It's about communicating the intellectual pleasure of wrapping your head around thesefundamental bits of computer science, and in that respect it succeeds admirably. If you're looking for an introduction to the area, this is definitely worth getting hold of.

Accessible discussion of algorithm topics implemented in Perl
If you have ever studied algorithms and data structures, then balanced trees and O(N) notation may still be a painful memory. Also, part of Perl's strength is in its built in parsing and sorting features so why would you need to know other ways of doing the same job? If your work does not challenge Perl's features then you probably do not need this book. However, if you have no computer science background and Perl is your language of choice then this book requires serious consideration.

The book is concise and the advice given in concepts like choosing an appropriate data structure or in benchmarking your program is actually quite sound. It covers a wide number of topics such as sorting, searching, sets and matrices together with material you may not find in a data structures book like geometry, cryptography and statistics.

Your choice depends on the task at hand. If you're looking for a Perl book where you can find routines to encrypt a string or find the maximum distance between two points then this book will not disappoint. Indeed, I believe that anyone serious about programming would benefit greatly from some of the Computer Science subjects discussed and implemented in Perl that are offered in this book.

Good implementation of popular algorithms
Klowledge of algorithms and data structures is vital for effective programming, and Perl is one of the most popular programming languages around, so this book fills a long-needed niche.

If you've ever looked at "Introduction to algorithms " by Cormen et al (CLR), this book will look familiar. It covers many of the topics covered in CLR, though not in such theoretic depth. It does, however, have mountains of Perl code implementing those algorithms.

This book can seemingly have two purposes - one is to learn algorithms (as the title suggests), and the other is to understand the implementation of algorithms in Perl.

IMHO, the authors fulfilled the second part quite well. For the first part, CLR is a excellent book and is hard to better. I don't think "Mastering algorithms" explained the topics in a clear enough way to compete with CLR, but it can indeed be a terrific companion to CLR (get the first edition, used copies cost pennies). Read about the algorith m in CLR, understand it from the pseudo-code and diagrams, then take "Mastering algorithms with Perl" and learn the Perl implementation of the algorithm.

A great book on the subject
This book is a great book, not only on the subject of algorithms, but also on how to implement them in Perl.A huge number of topics are covered, from Data Structures, to Searching/sorting, to cryptography, and much more.And what I found to be among the most useful additions was that for every subject, they give you a full implementation on the subject.I've read a few books on algorithms, but this is one of the most easy to read, and definitely one of the most practically useful.Recommended for any Perl programmer, regardless of skill.

MAP makes many promises, but fails to deliver.
As a guy ( engineer not computer expert ) who uses computers everyday to help his research, I would steer you away from using Perl for any task involving mathematical concepts more complicated than addition/subtraction/multiplication and addition.

I heard this same advice before buying this book and ignored it, I really wish I had listened back then.

While MAP has some nice pictures which broadly describe the essential concepts, it will give you no idea as to how to actually implement those ideas. Further, all the code is available in CPAN ( If you don't know CPAN, check it out before going any further - at the very least install a module ) and much ( at least what I attempted to use ) appeared to be broken.

Authors of computer books are usually good about answering e-mail but these authors did not deign to respond to mine.

If you are out there, struggling to learn algorithms, I would suggest taking a good computer course on the subject. I'm 99% certain the course will be taught in C/C++ or similar language -these languages have tremendous advantages over Perl when it comes to data structures and, believe me, even as a novice I've come to appreciate them...

If you really know algorithms and wish to write a few in Perl, you can do without this book. Pick up Deitel & Deitel's 'Perl: How to Program' instead or O'Reilly's basic book ( which is good, but I prefer Deitel and Deitel ) ....besides D&D answer their e-mail. ... Read more

Product Description
Although traditional texts present isolated algorithms and data structures, they do not provide a unifying structure and offer little guidance on how to appropriately select among them. Furthermore, these texts furnish little, if any, source code and leave many of the more difficult aspects of the implementation as exercises. A fresh alternative to conventional data structures and algorithms books, A Practical Guide to Data Structures and Algorithms using Java presents comprehensive coverage of fundamental data structures and algorithms in a unifying framework with full implementation details. Recognizing that software development is a top-down process, this applications-centered book provides careful guidance to students and practitioners.

Complete and thoroughly integrated Java implementations expose key differences among a wide range of important data structures, including many useful abstract data types not provided in standard Java libraries. Fundamental algorithms appear within the context of their supporting data structures. Case studies, examples, decision trees, and comparison charts throughout the stylized presentation illustrate and support an efficient methodology for the careful selection and application of data structures and algorithms. Appendices summarize major features of the Java programming language, introduce asymptotic notation and complexity analysis, and discuss design patterns applied in the book.

A true marriage of theory and practice, this book sets a new standard as a comprehensive practical guide to data structures and algorithms. Practitioners and students will reach for this book often to quickly identify the best data structure or algorithm for their applications. ... Read more

Customer Reviews (2)

Outstanding Text
If you are looking for a book that introduces the most fundamental concepts in computer science, this is the one.Sufficiently well written for the motivated student to teach themselves, and the best course textbook for scaffolding students with a wide range of preparation (from the novice to intermediate CS student).

Very well written.

Very hands on
This is a very hands on books..has lots of good exercises...could be better but comparing data structures is the best section in it ... Read more

Product Description
(Pearson Education)Text providing a comprehensive introduction to important algorithms in C, concentrating on graph algorithms. Covers diagraphs and DAGs, shortest paths, minimum spanning trees, network flows, sample C code, and detailed algorithm descriptions. Previous edition not cited. Softcover. DLC: C (Computer program language). ... Read more

Customer Reviews (4)

Excellent figures, average analysis
This is a great book for the reader interested in learning a collection of graph algorithms. Though the C code isn't very clear, the text makes up for it with concise well-written explanations. And the figures do an excellent job of illustrating the execution of the algorithms.

But the problem is that it's not so great a book to study the properties of those algorithms. Most theorems are way too dense and the author relies too much on English explanations, when algebraic expressions would be a lot more explanatory. Sometimes the reader gets a sense that the author is hand-waving instead of giving proper proofs.

I'm fed up with these books
I bought these two book for one reason: to get help implementing algorithms. Since there is lot of code in these books, I thought this would be a good pick. I was wrong. The author is consistently leaving out details vital to understanding the code. He also makes a big deal about abstract data types. This is gloriously of the case. If the readers are supposed to understand the code, transperency would be a more intelligent goal for the author. There are no comments in the code what so ever (yes, this is actually true, not even in the on-line code). The on-line code to this book is a total mess. You would be able to implement all the algorithms from scratch in less time than it would take you to try and piece together the code the author has left for you.
The pity is that there are very few other algorithm books that have real code. Demand a new edition from the author and don't by this one unless you can avoid it.

Better then no book about graph algorithms.
Robert Sedgewick is certainly well known to all people involved in the development of algorithms form different fields as an author of a number of books about algorithmic methods and data structures. And I am sure that we all appreciate this work because one simply needs all the time a reference to look up not only how one can solve a probem algorithmic but also how one can do this in an efficient way.

This book provides a good overview of algorithms dealing with graphs but the problem is that the connection between the given source code in C and its general exlanation failed. It is clear, that a solution to a problem does not depend on the underlying programing language, hence, Sedgewick's book is anyway not intened to do this otherwise it would wear another title. On the other hand, an algorithm without general explanation brings not much.

I think this book has a conceptual problem. None is interested in preimplemented code, because one normaly has a certain problem the algorithm has to be adapted. In general, this book is better then nothing but far from being a complete source of information concerning the functioning of the algorithms.

A must-have reference for Graph Algorithms
As students in Robert Sedgewick's Algorithms and Data Structures Course at Princeton, we had the privilege of reading Part 5 of Algorithms in C in a preprint edition this spring. Its treatment of Graph Algorithms is as thorough and comprehensive as the treatment of sorting and searching in parts 1-4.The algorithms discussed range from the fundamental (Depth-first search, Dijkstra's algorithm), to the relatively obscure (Gabow's strong component algorithm), to the impossibly difficult (Network Simplex), all in great detail.The book also discusses real-world applications of these algorithms, such as arbitrage. It contains a good number of useful diagrams allowing step-by-step traces of the algorithms, which helps decipher the sometimes cryptic code.
A warning: the book is DENSE. It is packed with detailed information and can be a difficult read, especially the mathematical analysis of the algorithms.

All in all, a great book, though. ... Read more

Product Description

The first textbook that focuses purely on Synchronization - a fundamental challenge in Computer Science that is fast becoming a major performance and design issue for concurrent programming on modern architectures, and for the design of distributed systems.

Customer Reviews (2)

One of the best books on the item
The book gives an excellent description for advanced topics in synchronization problems( at least this topics are advanced for an ordinary engineer who has hardly encountered something beside read-write spin locks and semaphores ). In my opinion one of the most interesting chapters are those that include theorems which give a low space boundary posed by the properties of objects used for synchronization.
The book is on the same level as Herlihy and Shavit's "The art of multiprocessor programming". I would recommend to read the both - it is hard to choose the better one, they both are excellent.

Excellentbook for concurrent programming
The book introduces the fundamental concepts of concurrent programming and presents synchronization methods and techniques used for solving numerous problems in programming multiprocessor (multicore) computer architectures. It is written in a clear style that makes it a pleasure read. A superb academic treatment of the topic.
... Read more

Product Description
Data stream algorithms as an active research agenda emerged only over the past few years, even though the concept of making few passes over the data for performing computations has been around since the early days of Automata Theory. The data stream agenda now pervades many branches of Computer Science including databases, networking, knowledge discovery and data mining, and hardware systems. Industry is in synch too, with Data Stream Management Systems (DSMSs) and special hardware to deal with data speeds. Even beyond Computer Science, data stream concerns are emerging in physics, atmospheric science and statistics. Data Streams: Algorithms and Applications focuses on the algorithmic foundations of data streaming.In the data stream scenario, input arrives very rapidly and there is limited memory to store the input. Algorithms have to work with one or few passes over the data, space less than linear in the input size or time significantly less than the input size. In the past few years, a new theory has emerged for reasoning about algorithms that work within these constraints on space, time and number of passes. Some of the methods rely on metric embeddings, pseudo-random computations, sparse approximation theory and communication complexity. The applications for this scenario include IP network traffic analysis, mining text message streams and processing massive data sets in general. Data Streams: Algorithms and Applications surveys the emerging area of algorithms for processing data streams and associated applications. An extensive bibliography with over 200 entries points the reader to further resources for exploration. ... Read more

Customer Reviews (1)

An accessible, but too short, survey of an important area
The book lists a fair number of important problems in the rapidly developing area of data stream algorithms (algorithms for processing huge amounts of data in one or more passes without ever loading the entire dataset into memory, for example network traffic or webpage hits). Every problem is explained and then the author discusses the known ideas for solving this problem and gives references to papers where the solutions are presented in full. The book is very accessible, does not have a lot of math and has only the simplest outlines of algorithms and proofs (for others, the reader is sent to the original sources). This is both good and bad: it is more like a survey than like a textbook; I expected to learn more from the book itself. Anyways, as a survey the book is invaluable and I'm grateful to the author for producing it. Also, though I didn't learn many algorithms and proofs, I learn quite a few good ideas; the book is well-structured and ideas are presented explicitly. ... Read more

Product Description
This text is based on a simple and fully reactive computational model that allows for intuitive comprehension and logical designs. The principles and techniques presented can be applied to any distributed computing environment (e.g., distributed systems, communication networks, data networks, grid networks, internet, etc.). The text provides a wealth of unique material for learning how to design algorithms and protocols perform tasks efficiently in a distributed computing environment. ... Read more

Product Description
This text, extensively class-tested over a decade at UC Berkeley and UC San Diego, explains the fundamentals of algorithms in a story line that makes the material enjoyable and easy to digest. Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal.

Features include:The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated.

Carefully chosen advanced topics that can be skipped in a standard one-semester course, but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence.

An accessible treatment of linear programming introduces students to one of the greatest achievements in algorithms.An optional chapter on the quantum algorithm for factoring provides a unique peephole into this exciting topic.In addition to the text, DasGupta also offers a Solutions Manual, which is available on the Online Learning Center.

"Algorithms is an outstanding undergraduate text, equally informed by the historical roots and contemporary applications of its subject.Like a captivating novel, it is a joy to read."Tim Roughgarden Stanford University ... Read more

Customer Reviews (21)

Lacking Detail
From a student perspective, this book is a hit or miss.One example: Pg.12 "Ordinarily we would spell out the algorithm in pseudocode, but in this case it is so familiar that we do not repeat it." That algorithm is mentioned in an introductory Digital Logic class on how to do addition on the bit level.It is simple, but if you didn't know it you'd have to google it.Second example: Ch.3 Figure 3.7, 2nd figure is the result of running DFS on the first one.Nowhere does it mention what you do with edge A to F, and if we should ignore it or not in our output representation.I could go on and on.It will not kill authors to explain how they came to their conclusions in their examples - just a few sentences is all we students ask.My opinion on this book is mixed, but if you're going to use it just read it by a computer with the google page ready to go.You can almost certainly find better explanations from competent instructors.

A nice book
I bought this book just as a complementary reading and I enjoyed it. I think this book is more like a divulgation book about algorithms rather than a college text book about the subject, but it is a really good one.
If computers and programming are beginning to be one of the things you like, you should read this introductory book, it is really didactic.It is easy to read and follow. It explain the main idea behind each algorithm, also the Boxes are really informative and inspiring.
If you finished it, and you liked what you had read, you should continue whit Introduction to Algorithms by Cormen et al.(that one maybe be the most famous and used college text book about algorithms). And if you really enjoyed the parts that talk about graphs, paths, linear programming and complexity you should continue with another book of Papadimitriou & Steiglitz called Combinatorial Optimization: Algorithms and Complexity.
So this will be a nice easy reading book for that people that simply like thinking about algorithms.

Not a stand alone text for undergrads or those with little background
This book is rather thin on material to be used for introductory work which is more of a complaint with those that chose it for the course rather than the book. Against the book however, most ideas are either skimmed over quickly or vaguely alluded to even though they share a great deal of importance in building a comprehensive understanding. Additionally, many problems in the exercises section don't have sufficient material covered in the chapter to tackle them without additional knowledge.

Definitely not a stand alone text.

Algorithms
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.

As a student
I took this class as a student and I was not impressed at all by the text. The text is far too informal. The problems unchallenging. The algorithms uninteresting. The historical content was far too sparse. 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. ... Read more

Product Description
Evolutionary Algorithms in Engineering and Computer Science Edited by K. Miettinen, University of Jyväskylä, Finland M. M. Mäkelä, University of Jyväskylä, Finland P. Neittaanmäki, University of Jyväskylä, Finland J. Périaux, Dassault Aviation, France What is Evolutionary Computing? Based on the genetic message encoded in DNA, and digitalized algorithms inspired by the Darwinian framework of evolution by natural selection, Evolutionary Computing is one of the most important information technologies of our times. Evolutionary algorithms encompass all adaptive and computational models of natural evolutionary systems - genetic algorithms, evolution strategies, evolutionary programming and genetic programming. In addition, they work well in the search for global solutions to optimization problems, allowing the production of optimization software that is robust and easy to implement. Furthermore, these algorithms can easily be hybridized with traditional optimization techniques. This book presents state-of-the-art lectures delivered by international academic and industrial experts in the field of evolutionary computing. It bridges artificial intelligence and scientific computing with a particular emphasis on real-life problems encountered in application-oriented sectors, such as aerospace, electronics, telecommunications, energy and economics. This rapidly growing field, with its deep understanding and assesssment of complex problems in current practice, provides an effective, modern engineering tool. This book will therefore be of significant interest and value to all postgraduates, research scientists and practitioners facing complex optimization problems. ... Read more

Customer Reviews (1)

Excellent review of the status of GA's
This book is perfect to bring the practioner or researcher up to date with the state of the art in the field of GAs. Because each chapter is authoredby different contributors, the style varies a lot.However, the book succeeds in its unifying theme.Probably the most useful thing accomplished here is to introduce the research community to the reader so that one can pick up reading directly from the fast evolving literature. Enjoy. ... Read more

Product Description
This book emphasizes the creative aspects of algorithm design by examining steps used in the process of algorithms development. The heart of this creative process lies in an analogy between proving mathematical theorems by induction and designing combinatorial algorithms. The book contains hundreds of problems and examples. It is designed to enhance the reader's problem-solving abilities and understanding of the principles behind algorithm design. ... Read more

Customer Reviews (13)

a *creative* approach
This book is much more than a catalog of algorithms (e.g., CLR): its purpose is to train your intuition to recognize mathematical structure in abstract problems.What does it matter if you know Dijkstra's algorithm?It's much more valuable to have good intuitions and a inductive reasoning tool chest with which to smash apart all of the variations of the shortest path problem (for example.)

The reviewers who wrote that the book "assumes you are a math wiz" and that it provides "little or no guidance for solving an arbitrary problem of the same type" didn't get it.This book is trying very hard to make you into a wiz by forcing you to really interact with mathematics, rather than working through a set of nearly identical problems (--what passes for "education" in North America.)

I was just going to leave my review at that, but since the reviews that people find "helpful" are so way off base, I think I should throw in a relevant story.

When my friend was in grade 11, he showed up to the Canadian Computing Competition finals, placing 14th.The guy who won told him, "if you want to win, read this book."Two years later, he won the CCC against 2000 other students.This book is the best introduction you can give a budding mathematician.

Sure: you can cough up what you've memorized from CLR during your university algorithms course.But, do you want to learn to invent algorithms yourself?

Math is not something handed down generations in big, dry, textbooks.Like all knowledge, math is organically discovered Truth, and you have learn to discover it for yourself.

Complementary to the CLR.
I wonder why this book is not as popular as it should be. Although the CLR is the mandatory book of most introduction to algorithm classes, it does not say much of how they came up with those algorithms which is the role of this book. The unique interesting thing is it uses induction to explain how each algorithm was developed, however I guess it's not the primary objective of the author. He wanted readers to read the description of the problems that those algorithms try to solve, and learn to apply induction to solve them on their own. If you like solving puzzle, you will love it.

A great supplement and right sized for travel too!
I really like this book as a supplement to the algorithm bible (Introduction to Algorithms, Thomas Cormen et al).This book is tiny and portable yet every major algorithm is covered.Basics, like mathematical induction are reviewed and illustrated with relevant examples.

One of the ways that Udi Manber packs so much information into such a small package is by keeping verbosity to a minimum.In his proofs, only the most complicated steps are justified or explained.As a result the reader may find herself spending time justifying steps in the proofs that are unrelated to the problem at hand.I did not mind doing this;others may.Regardless, the persistent reader will find that within the pages of this book lies all of the information required to understand all of the algorithms covered (and of course, it never hurts to keep a notebook, pencil and several erasers handy).

I would not recommend this book as a reference;rather, it provides a refreshingly new perspective on algorithms that may seem old and dusty.I've spent more time and energy per page on this book than any other CS book I've had but the ROI has been well worth the effort.

thought that this book was wonderful, but...
...I changed my mind after trying to use this book alone to implement FFT.Its description is quite clear and simple, much simpler than the Rivest et al book or wikipedia.Unfortunately, though clear, it is not complete and it is not possible to actually implement FFT using this book alone.I ended up having to use the Rivest et al book (which I had on CD via DDJ) along with this book to implement it.(Wikipedia was truly hopeless for trying to understand the FFT algorithm.)I was able to implement FFT in a single page of Python code because of Manber's description.

For giving very simple explanations of a number of algorithms, this book is fantastic.Just don't rely on it for the technical details.

Great on algorithm design, not that good on analysis
I like this book a lot. I think it's a good reference and introductory text, maybe as a supplement. It's much easier to read than Cormen's, but not half as deep.

Pros:
- Easy to read. You can understand an algorithm much faster if you go to this book first.
- Good examples and pictures.
- Explain the ideas that lead to efficient algorithmic designs.

Cons:
- Doesn't go into enough details about the proofs of correctness and complexity.
- The approach is different than most books and may take some time to get used to. ... Read more

Product Description
This book offers a modern approach to computational geo-metry, an area thatstudies the computational complexity ofgeometric problems. Combinatorial investigations play animportant role in this study. ... Read more