Top positive review
19 people found this helpful
5.0 out of 5 starsGreat book but I received counterfeit copies
BySean Lawrenceon July 15, 2017
Buyer beware! Amazon appears to be selling counterfeit textbooks. I have notified Amazon of this problem and re-purchased and still received what I believe to be counterfeits due to the very poor quality of the color, binding, printing, and horrible misspellings on the back of the book in particular.
The contents of the book is great BTW. However I'd recommend buying direct from publisher.
The contents of the book is great BTW. However I'd recommend buying direct from publisher.
Top critical review
78 people found this helpful
3.0 out of 5 starsHigh hopes but a little disappointed
ByBHon October 7, 2015
I had high hopes for this book given the reviews here. I bought this book brush up on my existing knowledge and learn new things and was very excited to receive it. There are some interesting points and I liked that it has a section on heuristics. It introduced me to the idea of simulated annealing, which I am using for a problem at work now actually, but like most things in the book I had to turn to the internet for a better explanation. The book is a bit wordy and hard to read at times.
The other major gripe I had is with the code examples. Most variables and method parameters are named a, k, c .. etc. For instance here is a method header in the backtracking section: construct_candidates(int a[], int k, int n, int c[], int *ncandidates)
This makes the code very hard to read and follow as well when you are a lines deep in a method trying to figure out what
k[i] - c + a is. It has been my experience that most math/engineer types and professors tend to write code this way vs giving things descriptive names so the code is easily understandable. The book would be 10X more valuable had the code samples been clearer. I ended up sending it back.
The other major gripe I had is with the code examples. Most variables and method parameters are named a, k, c .. etc. For instance here is a method header in the backtracking section: construct_candidates(int a[], int k, int n, int c[], int *ncandidates)
This makes the code very hard to read and follow as well when you are a lines deep in a method trying to figure out what
k[i] - c + a is. It has been my experience that most math/engineer types and professors tend to write code this way vs giving things descriptive names so the code is easily understandable. The book would be 10X more valuable had the code samples been clearer. I ended up sending it back.
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ByJohn Pierceon March 23, 2016
Not sure why this is listed as "abridged" but the number of pages matches the other listing for the item. It took a fair amount of searching on the ISBN to find someone who disclosed the number of pages.
Personally, I really like Mr. Skiena's writing style and his presentation is clear. It's not as dry as Sedgwick. This has now become my favorite book on algorithms.
Personally, I really like Mr. Skiena's writing style and his presentation is clear. It's not as dry as Sedgwick. This has now become my favorite book on algorithms.
7 people found this helpful
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This text strikes a perfect balance between too complex and too simple-- with hundreds of practical techniques that give a great overview of nearly every type of algorithm problem we encounter. This is NOT a "theory" text about big Oh (although it has a chapter), efficiency, p vs np and advanced calculus and linear algebra, but does show practical ways to design algorithms and answer questions in that interview.
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.
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.
ByCameron Pietrafesoon January 27, 2013
I purchased this book (Kindle edition) to brush up on what I learned in Algorithms class over a decade ago. I found it has amazing and detailed information, and if I was teaching an algorithms course this would be THE text book. However, I found at times Skiena's presentation to unnecessarily complicate some of the material. Without a lecture to help clarify I found even myself getting confused. For this reason I can't give it 5 stars and would recommend watching MIT's video lectures on Algorithms first if you are a novice, and that should help enough to smooth over some of this book's rough edges in your mind. Other than that the "War Stories" are great tails of practical real-world algorithm solutions, and I loved the emphasis Skiena uses on proper data-structure selection for various algorithms and the comparison tables. I also liked the quick reference/cook-book chapter to aid in solving encountered problems.
ByAlexander Schnackenbergon June 18, 2015
If you've been sentenced with the CLRS book (Introduction to Algorithms), buy this book in addition!! CLRS has very firm technical descriptions, but The Algorithm Design Manual is simply much more enjoyable and provides a lot of the motivation for using some of the algorithms described in CLRS. The book is simply a delight to read.
ALSO: perhaps most importantly, if you are a recent graduate of a computer science program and you are trying to get a job in the field, this is the FIRST book I would recommend to review algorithms and data structures. DO NOT EVEN BOTHER to pick up CLRS (unless specifically directed to do otherwise), as more than likely the questions you will get during the interview will be some variation of the problems that you will encounter in here. I had at least one interview in which all of the problems were derivatives of those mentioned in here; unfortunately I had not yet found this book and so I was rather poorly prepared. When I first picked this up a few months later, I immediately recognized it's value and the fact that this was the only resource I had needed all along.
ALSO: perhaps most importantly, if you are a recent graduate of a computer science program and you are trying to get a job in the field, this is the FIRST book I would recommend to review algorithms and data structures. DO NOT EVEN BOTHER to pick up CLRS (unless specifically directed to do otherwise), as more than likely the questions you will get during the interview will be some variation of the problems that you will encounter in here. I had at least one interview in which all of the problems were derivatives of those mentioned in here; unfortunately I had not yet found this book and so I was rather poorly prepared. When I first picked this up a few months later, I immediately recognized it's value and the fact that this was the only resource I had needed all along.
ByRon Von September 24, 2016
It's not a great one to start off with, especially if you never did an algorithms class in college. I'd say it's a decent second book, as it has enough complexity, but it has a somewhat readable style. You can tell the author really tried to make the material approachable, but it's nowhere near as beginner friendly as the amazing book "Grokking Algorithms", that one is a true beginners book. This is a decent second one.
ByVivinon April 16, 2013
This book is great! For a lot of software engineers, you don't really end up dealing with data-structures or interesting algorithms; most of the time you're stuck in business logic. So it's easy to get rusty on your basic concepts. This book does a great job reintroducing those concepts to you. Even if you're a novice, this book is great. But if you've already had some exposure to CS-II/CS-III level concepts, then that is pretty helpful as well.
The author introduces the algorithms and data-structures in practical terms and so it is easy to relate to them instead of thinking of them as purely abstract and theoretical. I especially liked the "war stories", where he shows you how he was able to apply theory in practice. What is great about this is that it lets you recognize the different problem domains and where you can apply specific algorithms and/or data-structures.
The second half of the book is essentially a catalog of different problems that you can encounter, and how you can solve them with specific algorithms/data-structures or variations thereof.
All in all, a great book and it is absolutely indispensable for a good software-engineer.
The author introduces the algorithms and data-structures in practical terms and so it is easy to relate to them instead of thinking of them as purely abstract and theoretical. I especially liked the "war stories", where he shows you how he was able to apply theory in practice. What is great about this is that it lets you recognize the different problem domains and where you can apply specific algorithms and/or data-structures.
The second half of the book is essentially a catalog of different problems that you can encounter, and how you can solve them with specific algorithms/data-structures or variations thereof.
All in all, a great book and it is absolutely indispensable for a good software-engineer.
ByNelson Eduardo Arapé Pérezon March 23, 2018
Very comprehensive guide through algorithms and data structures, with a lots of exercises and reference at the end of the chapter. But what I liked the most was the war stories: the author is a university professor and also a consultant so he present interesting war stories related to the content of the chapter.
On the down side I had to reread some explanations several times but most probably is because of the subject itself rather
On the down side I had to reread some explanations several times but most probably is because of the subject itself rather
ByWillon December 16, 2013
I read a blog post by Steve Yegge in which he recommended this book when reviewing for an interview at Google. Skiena gives a nice breakdown of data structures and algorithms in general in the first half of the book and the second half of the book contains many common problems and how to break them down to come up with the most effective algorithm. I very strongly recommend this book to anyone and everyone going through technical interviews and to students that are preparing for programming competitions.
ByDimitri Kon May 29, 2015
The content is good in general. There are some disadvantages though. One is the use of the C language (better than Assembler though). But the biggest problem is that the author has a very unclear manner to express himself. He tries to fit all explanation in one sentence with a complicated grammar, use professional slang, and forget about details. Some algorithms are simply impossible to reconstruct.
ByJohn Meekon December 7, 2017
Great book! I have had to read some sections twice to really let the concepts sink in to my understanding. He gives great insights into algorithm challenges he faced over the years....
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