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The Algorithm Design Manual 2nd ed. 2008 Edition
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This newly expanded and updated second edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficacy and efficiency. Expanding on the first edition, the book now serves as the primary textbook of choice for algorithm design courses while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students.
The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part, Techniques, provides accessible instruction on methods for designing and analyzing computer algorithms. The second part, Resources, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations and an extensive bibliography.NEW to the second edition:• Doubles the tutorial material and exercises over the first edition
• Provides full online support for lecturers, and a completely updated and improved website component with lecture slides, audio and video
• Contains a unique catalog identifying the 75 algorithmic problems that arise most often in practice, leading the reader down the right path to solve them• Includes several NEW "war stories" relating experiences from real-world applications
• Provides up-to-date links leading to the very best algorithm implementations available in C, C++, and Java.- ISBN-101849967202
- ISBN-13978-1849967204
- Edition2nd ed. 2008
- PublisherSpringer
- Publication dateOctober 13, 2010
- LanguageEnglish
- Dimensions7.01 x 1.69 x 9.25 inches
- Print length748 pages
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Editorial Reviews
Review
From the reviews of the second edition:
“This is a detailed and timeless book that I keep reaching for. A useful book that I can not keep access to long enough. It is a important book to have in your library. Unlike other algorithm books that I have the algorithms are written independent of any programming language.” (Mary Anne, Cats and Dogs with Data, maryannedata.com, April, 2014)
“The Algorithm Design Manual by Steven Skiena is aimed at two groups of people: students and professionals. … It is written in an informal style that I found pleasant and engaging. … The book’s unique structure makes it more likely to be immediately useful to the practitioner who has problem to solve and wants to quickly make progress. The book succeeds admirably. Would be helpful to the student who has never seen this material before. Overall, I recommend this book warmly.” (Neelakantan Kartha, The Book Review Column, 2011)
“Algorithms are the very heart of computing. This book is about right for most people. Each of the topics is treated in a readable informal style with lots of asides and accounts of personal experiences - ‘war stories’ in implementing algorithms. If you want to use it as a course textbook then there are lots of exercises at the end of every chapter. Highly recommended.” (Mike James, I Programmer, September, 2009)
"Addressing the main difficulties of solving problems, this book goes far beyond the design of algorithms. It is essential for scientists, engineers, and any professionals who aim to solve problems, with a noticeable emphasis on real problems. It will not only serve as a valuable undergraduate textbook, but it will also become an irreplaceable reference guide for most professionals in the area." (Carlos Linares Lopez, Computing Reviews, February, 2009)
"Skiena focuses on the practical aspects of algorithm design and use. This work fills an important gap in the knowledge of CS practitioners and students. This book is suitable as a text for an undergraduate algorithms class, but also as an invaluable reference for the practicing programmer. This second edition has updated the bibliography to include recent works, making it an extensive bibliography. The index is also thorough and very useful for finding specific problems." (William Fahle, ACM Computing Reviews, December, 2008)
"For a decade, Steven Skiena’s Algorithm Design Manual retained its title as the best and most comprehensive practical algorithm guide to help identify and solve problems. It is now available in an improved second edition that is worth buying simply for the updates. Every programmer should read this book, and anyone working in the field should keep it close to hand. Would I recommend it? Absolutely. This is the best investment a programmer or aspiring programmer can make." (Harold Thimbleby, Times Higher Education, November, 2008)
"My absolute favorite for this kind of interview preparation is Steven Skiena’s The Algorithm Design Manual. More than any other book it helped me understand just how astonishingly commonplace … graph problems are -- they should be part of every working programmer’s toolkit. The book also covers basic data structures and sorting algorithms, which is a nice bonus. Every 1 – pager has a simple picture, making it easy to remember. This is a great way to learn how to identify hundreds of problem types." (Steve Yegge, Steve Yegge’s Blog, March, 2008)
" The book is an algorithm implementation treasure trove, and putting all of these implementations in one place was no small feat. The list of implementations, an extensive bibliography make the book an invaluable resource for everyone interested in the subject." (ACM Computing Reviews)
From the Back Cover
....The most comprehensive guide to designing practical and efficient algorithms!....
The Algorithm Design Manual, Second Edition
"...the book is an algorithm-implementation treasure trove, and putting all of these implementations in one place was no small feat. The list of implementations [and] extensive bibliography make the book an invaluable resource for everyone interested in the subject." --ACM Computing Reviews
"It has all the right ingredients: rich contents, friendly, personal language, subtle humor, the right references, and a plethora of pointers to resources." -- P. Takis Metaxas, Wellesley College
"This is the most approachable book on algorithms I have." -- Megan Squire, Elon University, USA
This newly expanded and updated second edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficacy and efficiency. Expanding on the first edition, the book now serves as the primary textbook of choice for algorithm design courses while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students.
The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part, Techniques, provides accessible instruction on methods for designing and analyzing computer algorithms. The second part, Resources, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations and an extensive bibliography.
NEW to the second edition:
• Doubles the tutorial material and exercises over the first edition
• Provides full online support for lecturers, and a completely updated and improved website component with lecture slides, audio and video
• Contains a unique catalog identifying the 75 algorithmic problems that arise most often in practice, leading the reader down the right path to solve them
• Includes several NEW "war stories" relating experiences from real-world applications
• Provides up-to-date links leading to the very best algorithm implementations available in C, C++, and Java
ADDITIONAL Learning Tools:
• Exercises include "job interview problems" from major software companies
• Highlighted take-home lesson boxes emphasize essential concepts
• Provides comprehensive references to both survey articles and the primary literature
• Exercises point to relevant programming contest challenge problems
• Many algorithms presented with actual code (written in C) as well as pseudo-code
• A full set of lecture slides and additional material available at www.algorist.com
Written by a well-known algorithms researcher who received the IEEE Computer Science and Engineering Teaching Award, this new edition of The Algorithm Design Manual is an essential learning tool for students needing a solid grounding in algorithms, as well as a special text/reference for professionals who need an authoritative and insightful guide. Professor Skiena is also author of the popular Springer text, Programming Challenges: The Programming Contest Training Manual.
About the Author
Steven Skiena is Professor of Computer Science at Stony Brook University. His research interests include the design of graph, string, and geometric algorithms, and their applications (particularly to biology). He is the author of four books, including "The Algorithm Design Manual" and "Calculated Bets: Computers, Gambling, and Mathematical Modeling to Win". He is recipient of the ONR Young Investigator Award and the IEEE Computer Science and Engineering Undergraduate Teaching Award.
Product details
- Publisher : Springer; 2nd ed. 2008 edition (October 13, 2010)
- Language : English
- Paperback : 748 pages
- ISBN-10 : 1849967202
- ISBN-13 : 978-1849967204
- Item Weight : 2.86 pounds
- Dimensions : 7.01 x 1.69 x 9.25 inches
- Best Sellers Rank: #371,394 in Books (See Top 100 in Books)
- #57 in Discrete Mathematics (Books)
- #222 in Data Processing
- #433 in Software Development (Books)
- Customer Reviews:
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About the author

Steven S. Skiena is Distinguished Teaching Professor of Computer Science at Stony Brook University. He is the author of six well-regarded books: The Algorithm Design Manual (2020), The Data Science Design Manual (2017), Who's Bigger (2013), Calculated Bets: Computers, Gambling, and Mathematical Modeling to Win (2001), Programming Challenges (with Miguel Revilla, 2003) and Computational Discrete Mathematics (with Sriram Pemmaraju, 2003).
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As an example, older calculators always started "high" when finding quadratic factors or square roots. Skiena (p. 134) shows that three possible "front ends" can make subsequent iteration (trial and error until you're done) faster and more efficient: 1. The older always start high method 2. A common bisection technique-- split the problem, then, by "divide and conquer" go higher or lower and 3. Use interpolation to get closer sooner, then iterate.
The book is set up both as a self study and year long course text, but frankly the presentation is far from academic and much more rubber hits the road practical, realistic, design. The background is given with pseudocode, then the basic level of math needed to get the job done without pages of theory and proofs of Big Oh efficiency, etc.
Since 2008, the next edition in 2010, and this 2012 "printing corrections" edition (not considered a true edition, but contains many detailed corrections), this book has found a great audience in interview prep, because the author takes such a real world approach to solutions. Make sure you get the corrected edition if you buy from an Amazon third party vendor, you will if you get it directly from Amazon.
Highly recommended for all levels of programmers. The index also has been updated, and some of the previous reviews pointing out errors corrected, making this an outstanding reference. As if 700 pages weren't enough, the author also provides 19 sections of practical reviews of online resources and a detailed 43 page very current bib. If you're looking for a difficult to find "vein" of info (say, for example, on CAS algos), you'll find a wealth of info in these sections. Many volumes call themselves cookbooks, this really IS the best of that genre. If you can afford only one algo book, and want to use it without a tutor, teacher or coach, this is the one. Don't take that to mean it's simple-- it's just as deep as the academic texts, but simply removes all the math you don't use every day anyway. It's really more for programmers than researchers, but researchers would still learn a lot about how practical algo writers frame problems.
Library Picks reviews only for the benefit of Amazon shoppers and has nothing to do with Amazon, the authors, manufacturers or publishers of the items we review. We always buy the items we review for the sake of objectivity, and although we search for gems, are not shy about trashing an item if it's a waste of time or money for Amazon shoppers. If the reviewer identifies herself, her job or her field, it is only as a point of reference to help you gauge the background and any biases.
Most books on algorithms take a very formal, math heavy approach in which they present, analyze and prove things about a somewhat arbitrary collection of algorithms. There's usually no mention of real world applications.
This book, however, takes a different approach, and serves as a guide book for using algorithms in the real world. There's a heavy emphasis on formulating problems in terms of existing, solved problems. If you can "map" your problem to one with a known solution, then you can use the proven, existing solution to solve your problem. To emphasize that point, roughly the entire second half of the book is a catalog of known problems and solutions, with references to software libraries, books and other sources of information.
I also love that the example code is in C. Too many books give example code in languages with a lot of overhead, like Java, and end up obscuring the important parts with a ton of object-oriented crap. Yes - OOP is nice, but unless I'm reading a book on OOP, I don't want to dig through 30 lines of irrelevant boilerplate just to find the 10 lines relevant to the algorithm.
That said, it's not the best code in the world. Some of the snippets could be explained better. And there were a few stylistic issues, such as leaving off function return types and a bunch of global variables, that I didn't like, but I'm willing to forgive those because it's not a book on C, and the lack of syntactic clutter made the algorithm easier to see.
I also thought chapter nine was a bit too long. A good portion of the chapter is spent reducing various NP-complete problems to other NP-complete problems. Interesting, but it was a bit too theoretical, and didn't really fit with the with the rest of the book.
(1) Splines --> p. 294 --> Intro to numerical problems with no reference to splines.
(2) Lisp --> p. 409 --> Section on (un)constrained optimisation - no Lisp.
(3) Linked lists -->
(3a) only mentioned in terms of linked lists vs arrays. Correct on p. 368
(3b) p. 72 --> Section stacks/queues or dictionaries. It should refer to pg. 70
My only other complaint (so far) is rather minor and came about while reading the first chapter. In particular, section 1.3.4 on Induction and recursion where the author attempts to use induction in order to prove some function Increment(y). Technically the author is using strong induction and not mathematical induction.
These are just some of the examples of how Springer and their talented editorial staff goofed up, not a representative picture meant to portray the book as an overall failure. As mentioned previously, I would highly recommend this book provided you can get over a faulty index and are not overly pedantic when it comes to someone elses use of Mathematical terminology.
Top reviews from other countries
- Real life war stories of optimizing algorithms to solve a practical problem.
- Algorithms from most if not all CS fields.
- A manual per problem where it gives the algorithm needed to solve the problem.
Fir me this is the best DS&A book, for anyone that wants something more practical than academic.
If you want something much more theoretical, buy CLRS instead. Personally, I'm planning buying CLRS too, because both are useful but for different reasons. CLRS is an encyclopedia of algorithms. Skiena's book is a swiss army knife that will get you out from a tough spot in real life.




















