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The Design and Analysis of Computer Algorithms, by Alfred V. Aho, John E. Hopcroft, Jeffrey D. Ullman
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With this text, you gain an understanding of the fundamental concepts of algorithms, the very heart of computer science. It introduces the basic data structures and programming techniques often used in efficient algorithms. Covers use of lists, push-down stacks, queues, trees, and graphs. Later chapters go into sorting, searching and graphing algorithms, the string-matching algorithms, and the Schonhage-Strassen integer-multiplication algorithm. Provides numerous graded exercises at the end of each chapter. 0201000296B04062001
- Sales Rank: #623399 in Books
- Published on: 1974-01-11
- Original language: English
- Number of items: 1
- Dimensions: 9.00" h x 1.40" w x 6.20" l, 1.51 pounds
- Binding: Paperback
- 470 pages
From the Back Cover
With this text, you gain an understanding of the fundamental concepts of algorithms, the very heart of computer science. It introduces the basic data structures and programming techniques often used in efficient algorithms. Covers use of lists, push-down stacks, queues, trees, and graphs. Later chapters go into sorting, searching and graphing algorithms, the string-matching algorithms, and the Schonhage-Strassen integer-multiplication algorithm. Provides numerous graded exercises at the end of each chapter.
0201000296B04062001
About the Author
Alfred V. Aho is Lawrence Gussman Professor of Computer Science at Columbia University. Professor Aho has won several awards including the Great Teacher Award for 2003 from the Society of Columbia Graduates and the IEEE John von Neumann Medal. �He is a member of the National Academy of Engineering and a fellow of the ACM and IEEE.
�
Monica S. Lam is a Professor of Computer Science at Stanford University, was the Chief Scientist at Tensilica and the founding CEO of moka5. She led the SUIF project which produced one of the most popular research compilers, and pioneered numerous compiler techniques used in industry.
�
Ravi Sethi launched the research organization in Avaya and is president of Avaya Labs.� Previously, he was a senior vice president at Bell Labs in Murray Hill and chief technical officer for communications software at Lucent Technologies. He has held teaching positions at the Pennsylvania State University and the University of Arizona, and has taught at Princeton University and Rutgers.� He is a fellow of the ACM.
�
Jeffrey Ullman is CEO of Gradiance and a Stanford W. Ascherman Professor of Computer Science at Stanford University. His research interests include database theory, database integration, data mining, and education using the information infrastructure. �He is a member ofthe National Academy of Engineering, a fellow of the ACM, and winner of the Karlstrom Award and Knuth Prize.
�
Ullman is the Stanford W. Ascherman Professor of Computer Science at Stanford.
Most helpful customer reviews
5 of 5 people found the following review helpful.
One of 2 books you will ever need on algorithms
By Rakesh
This book and Intro to Algorithms by Corman are perhaps the best 2 books in my hand. All you will ever need to form a firm foundation in algorithms are developed in these 2 books.
I had this book from way back when I was doing by Comp Sci. But recently, I lost this one during a move and had to re-order. So I though I would share my thoughts on it.
This one is much more formal when compared to Corman. However, I find it much easy to follow than Corman's. Also, I find that it becomes even better when you accompany it with some of the implementation books such as Algorithms in C etc.. It would be easier to visualize things when you accompany such a "practical" book along with this one.
TAOCP book could be another one. But I was exposed to these 2 books first before the TAOCP. I find that these 2 books put much heavy emphasize on the algorithms while the TAOCP brings in some of the other programming/dicreet math components that you study anyway in junior classes.
Draw back is that, the material is dated. Obviously, since they were published way back. So some of those optimal algorithms are not so optimal anymore. Both books lacks clear practical approach to some of those very important algorithms used today, especially on processing Graphs, Extendible Hash, Edge Detection, Concurrent Cache Oblivious B Trees etc... Concurrency is a big part of the world today. So I believe, if anyone where to make another books for academic or otherwise on algorithms, these items would be a prerequisite.
For a pure algo book on some of the core fundamental concepts, I have found much success even today with these 2 books. I don't think there are any books that can do better.
22 of 23 people found the following review helpful.
Yet another CS classic
By Ganapathy Subramaniam
This is yet another classic from the Aho Gang!
It sets up a very formal framework for discussing alorithms, beginning at the beginning..an abstract mathematical model of a computer. and builds up the rest of the book using the model for implementation as well as quantification.
A solid framework for the analysis of algorithms is setup. The necessary mathematics is covered, helping in measuring an algorithm's complexity..basically the time and space complexities.
Then it goes on to deal with designing algorithms. the design methodology, with elaborate examples and exercises.
It should be admitted however that this is a solid text for the mathematically oriented. Thats the reason for the 5 stars!
If you want to go a little easy on the formalisms try
"Computer Algorithms, Pseudocode" by Ellis Horowitz, Sartaj Sahni, Sanguthevar Rajasekaran. I found it more pragmatic.
6 of 7 people found the following review helpful.
Very effective introduction to algorithms
By Mike W.
The book used in my graduate Intro to Algorithms course, and I think the follow-on. While I am obviously not as well read in this subject as many of the other reviewers, I can say "it worked", and indeed worked well. A course that has a weak text or teacher will not inspire... A-H-O/DACA and Prof. Carlson made the material exciting, even to an "architecture guy". My interests in grad school in the early 80's revolved around tessellation automata (aka systolic arrays and other highly regular compute structures) and big steaming fast computer structures. A-H-O provided me with the best understanding of the kinds of problems faced by the computers which interested me the most, and the kinds of tools needed to understand computational impact and algorithmic structuring of solutions to them. I sincerely with I hadn't lost my copy with the hundreds of annotations in the margins.
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