- Series: In a Nutshell
- Paperback: 390 pages
- Publisher: O'Reilly Media; 2 edition (April 2, 2016)
- Language: English
- ISBN-10: 1491948922
- ISBN-13: 978-1491948927
- Product Dimensions: 5.9 x 0.8 x 8.9 inches
- Shipping Weight: 1.1 pounds (View shipping rates and policies)
- Average Customer Review: 5 customer reviews
- Amazon Best Sellers Rank: #39,996 in Books (See Top 100 in Books)
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Algorithms in a Nutshell: A Practical Guide 2nd Edition
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About the Author
George Heineman is an Associate Professor of Computer Science at WPI. His research interests are in Software Engineering. He co-edited the 2001 book "Component-Based Software Engineering: Putting the Pieces Together". He was the Program Chair for the 2005 International Symposium on Component-Based Software Engineering.
Gary Pollice is a self-labeled curmudgeon (that's a crusty, ill- tempered, usually old man) who spent over 35 years in industry trying to figure out what he wanted to be when he grew up. Even though he hasn't grown up yet, he did make the move in 2003 to the hallowed halls of academia where he has been corrupting the minds of the next generation of software developers with radical ideas like, "develop software for your customer, learn how to work as part of a team, design and code quality and elegance and correctness counts, and it's okay to be a nerd as long as you are a great one." Gary is also a co-author of Head First Object-Oriented Analysis and Design.Gary is a Professor of Practice (meaning he had a real job before becoming a professor) at Worcester Polytechnic Institute. He went to WPI because he was so impressed with the WPI graduates that he's worked with over the years. He lives in central Massachusetts with his wife, Vikki, and their two dogs, Aloysius and Ignatius. When not working on geeky things he ... well he's always working on geeky things. You can see what he's up to by visiting his WPI home page at http://web.cs.wpi.edu/~gpollice/. Feel free to drop him a note and complain or cheer about the book.
Stanley Selkow received a BS in Electrical Engineering from Carnegie Institute of Technology in 1965, and then a Ph.D. in the same area from the University of Pennsylvania in 1970. From 1968 to 1970 he was in the Public Health Service at the National Institutes of Health at Bethesda Maryland. Since 1970 he has been on the faculty at universities in Knoxville TN and Worcester MA, as well as Montreal, Chonqing, Lausanne and Paris. His major research has been in graph theory and algorithm design.
Top customer reviews
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On the negative side, the book seems like a dumbed down version of Cormen. But I think this a good thing. With such killer visuals these guys can write about anything and get is right. I am studying for programming interviews now, and this is a good refresher.
It was a poor choice - even if it was for free, this book is not worth your time. I read this book at the same time as several other algorithm books and this stood out by far as the worst, even compared to free books like a competitive programming handbook that was popular on hackernews at the time.
(1) The writer spends WAY too much time on examples, and on a couple particular example problems he's in love with. I would say maybe 20% of the book is the actual content you came here to learn (generalizable lessons about algorithms and data structure) and the other 80% are these examples that are obviously intended to train you to "think in algorithms" but are too poorly structured to do so.
(2) The worst part is that the wheat is completely buried in the chaff. There's no consistent delineation of concepts and examples - to get to the general principles you will have to wade through the poorly written examples. Skimming is impossible with this book
(3) When there are general concepts explained, they are explained in a "this is right because it is" way - there is no attempt to connect concepts, the ideas and takeaways that are thrown at you are seemingly random.
(4) The writing is ultimately just bad and doesn't feel topical. The writer does not make an effort to explain themselves clearly and most of the time it feels like they're not trying to teach about algorithms as a broad subject, or prepare you for recognizing and solving these problems; instead they just have a few whiteboard problems they really like to talk about, and along the way they'll pepper in a couple general points about algorithms.