algorithm analysis books

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6 comments, last by nilkn 18 years, 9 months ago
I would love to learn more about algorithm analysis, preferably asymptotic analysis. Not so much as to help me out in my programming projects, but moreso just for something to do when I'm bored (and I often am in the summer). Anyway, I'm thinking of buying a book. As it stands I know very little to nothing about algorithm design and analysis, so obviously I'm tending towards the introductory books. Right now the most likely candidate for purchase is Introduction to the Design and Analysis of Algorithms by Anany V. Levitin. Does this book look OK to get started with? I would think so judging by it's relatively high rating at Amazon, but I just want to make sure. Thanks a lot for your help.
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I'm not really feeling well enough today to think too deeply about something like algorithm analysis, but I'll help as best as I can...

I haven't read Levitin's book, and I'll admit I haven't really got a favourite book that is totally dedicated to algorithmic analysis. Most of the skill I got in looking at algorithms came from my textbooks such as Sudkamp's "Languages and Machines", Sedgewick's "Alogrithms in C" and Russel and Norvigs "Artificial Intelligence: A Modern Approach". And without Amazon giving me a quick peek at the table of contents of the book, I'm not sure how good it looks. It does have 5 stars, but only 4 reviews.

However, like a lot of textbooks, it has a really hefty price. $90 U.S. dollars is quite a lot. If you're really keen on algorithmic anaysis, not afraid of some hardcore maths (which you really need for algorithmic analysis) and have a bit more cash, maybe it would be better to spend a tiny bit more and get the definitive work: "The Art of Computer Programming" by Donald Knuth. You can get the hardcover boxed set of Volumes 1 to 3 from Amazon for $US104.
I was born and lived with Introduction to Algorithms by Cormen, Leiserson and Rivest.
This book covers it all. Algorithms, data structures, and underlying math.
It's also its fourth(fifth?) edition by now. So I think it's kinda reliable.

I've read Knuth's "Art of Programming". It's good, but the amount math used by the author is enormous IMO. Got somewhat bored after a few "deep analisis".

Cheers.
/def
I use Data Structures and Algorithm Analysis by Mark Allen Weiss. Versions are available in C,C++ or Java (there's also an out of print ADA version).
Thanks for your suggestions.

I've decided to just go to Barnes and Noble and skim through the books themselves to make my decision, rather than just relying on Amazon reviews.

I've already looked at "Art of Computer Programming" and found the math to be too heavy for my taste, so right now I'm looking at "Introduction to Algorithms", as it seems like it covers a broad range of topics.

Thanks again!
I have to second the recommendation for CLR's "Introduction to Algorithms." It's incredibly thorough and detailed, and is worth every penny.
Orin Tresnjak | Graphics ProgrammerBethesda Game StudiosStandard Disclaimer: My posts represent my opinions and not those of Bethesda/Zenimax, etc.
Quote:Original post by deffer
I was born and lived with Introduction to Algorithms by Cormen, Leiserson and Rivest.
This book covers it all. Algorithms, data structures, and underlying math.
It's also its fourth(fifth?) edition by now. So I think it's kinda reliable.

I've read Knuth's "Art of Programming". It's good, but the amount math used by the author is enormous IMO. Got somewhat bored after a few "deep analisis".

Cheers.
/def


Seconded! Although the book is only in it's second edition, they improved the book quite a bit. As long as you have a decent math background, this book is great.

"What are you trying to tell me? That I can write an O(N^2) recursive solution for a 2-dimensional knapsack?" "No, programmer. I'm trying to tell you that when you're ready, you won't have to." -Adapted from "The Matrix"
I went out to Barnes & Noble and ended up buying "Introduction to Algorithms", as it looked the best, and the math wasn't too intense for me. 1180 pages of analytical goodness!

Thanks again for your suggestions.

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