Customer Reviews

The Algorithm Design Manual

5 star:		(15)
4 star:		(6)
3 star:		(1)
2 star:		(1)
1 star:		(1)

 

 

My Dad loved to cook and one of his favorite cookbooks was "The Joy of Cooking." By the time he died, the pages of his copy were stained and dusted with flour from being constantly used in his kitchen.

Why did he like it so much? Because not only did it have great recipes, it also explored the basic ingredients and methods and told interesting stories about cooking.

That's why "The Algorithm Design Manual" could be called "The Joy of Algorithms." Not only has it become my "goto" book for finding the right algorithmic approach to a problem, it is a joy to read with Skiena's "war stories" and his lively writing style.

Just like my Dad's "The Joy of Cooking" was never far from his stove, "The Algorithm Design Manual" will never be far from my computer.

I've got the Cormen book as well, which I love. This book is a much more readable text, by far. I think that others here have broken down the areas covered quite well; so I'll just give a stream of consciousness version of what I liked about the book.

It gives the subject matter with from a need to know standpoint. It also gives you real world examples of how the author has had to utilize algorithms not just to implement a particular solution, but to also optimize existing solutions. Although it doesn't give the hardcore theoretical breakdowns in Cormen's text, don't think that the subject matter is presented in a lightweight format. You will still be given some level of mathematical proof for some algorithms and data structure optimizations.

Although less terse than the typical text on Algorithms, it doesn't try too hard to be cute and quirky. The humor is well placed and not too overbearing.

Though less academic than "Introduction To Algorithms", this ain't the book to pickup to learn about coding algorithms for a quick study prior to an interview. However, if you're planning to get ready for interviews maybe a few months down the road...go for it!

A caveat...I got the Kindle version for the Android, which is none too forgiving when it comes to images. So diagrams look horrible on the phone (even with the DroidX's big-assed screen). It looks fine on the laptop, however.

Enjoy!

I needed to understand some best fit algorithms and alternatives without reading a whole numbing book. The organization of this book and the right level of detail help me get there.

I recently bought the second edition in order to do some personal research and, as such, did not plan on reading the book from cover-to-cover. I intend to use the book as a reference and therefore utilize mainly the index and, to a lesser extent, the table of contents. Yes the material is this book is, in general, sufficient, but the index is bogus. The following presents some examples in order to valid my claim (again, I am referring to the second edition and I am NOT making any claims against the first edition):

(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.

This book is by far the best algorithms book I've read.

Two major reasons for this: the sections include many considerations when choosing algorithms/data structures, and the number of war stories showing how such decisions were made in real situations.

I would recommend this text to anyone that writes software seriously.

The first part of the book gives a nice overview of algorithms, with some interesting examples and inspiring war stories. It is a nice read, and it should help a beginner get some feeling of what is and isn't important in solving programming problems.

Second part of the book (the "catalog") provides an extensive list of problems, each of them supported by recommendations on algorithms to apply when solving them. However, this part is not that detailed, and it often references variations of algorithms not covered in the book. Nevertheless, you will find guidance for many of the common tasks you are to encounter, which will be helpful to be aware of when you encounter similar problems.

I've read through the first half of the book, and am now at the catalog of algorithms that makes up the second half, and I've really enjoyed the book so far.

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.

I've been working with this book for a few weeks now. I had a specific problem in graph theory that I needed to solve and this book provided the concrete algorithmic analysis and solution options that I was looking for. In the process of researching that topic I encountered a treasure trove of other subject areas; the more I read the more I fell in love with this book. It really belongs on the bookshelf of every software practitioner, beginner and expert alike. It's a vital reference.

The writing style is clear, the math straightforward, and the catalog of solutions par excellence. The experience base of the author is impressive to say the least and he shares some fascinating real-world perspectives through his war stories. I highly recommend this book. By the way, get the hardcover version of the 2nd edition, not the paperback. For some reason Amazon is charging $71.24 for the paperback and $63.49 for the hardcover.

I love this book. It is very well written with thorough explanations, examples, applications, war stories and additional catalogs of "problem->algorithm" reference. The book is packed with real world applications of the algorithms, so it's very interesting to read, as opposed to dry explanations in other books. (For example, finding a center of the graph with Floyd-Warshall's algorithms can be used to find the best location to open, say, a Fedex Hub, or a restaurant.) I recommend it to every software engineer, both for the everyday use and for interview preparation. Every decent software engineer should know the stuff in this book. My husband thought the book was not clear when he skipped the theory chapters and tried reading only catalogs, but after I praised the book to him over and over, he finally read the meat of the book (pre-catalog chapters), and he loves it now.

Just reading this book I remembered why software is so interesting.

This is the second DS & ALG book after Drozdek that I can honestly say is great. All the finer points of the subject are explained in language you can understand, followed by snippets of relevant C code and big O analysis. This is like heaven for intermediate to senior Software Engineers. Someone who understands the subject extremely well can convey his thoughts without arrogance or sloppy code. Yes!!