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The Algorithm Design Manual
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This volume helps take some of the "mystery" out of identifying and dealing with key algorithms. Drawing heavily on the author's own real-world experiences, the book stresses design and analysis. Coverage is divided into two parts, the first being a general guide to techniques for the design and analysis of computer algorithms. The second is a reference section, which incl
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Showing 1-30
May 30, 2011
Ivan
rated it
it was amazing
·
review of another edition
Recommends it for:
anyone interested in algorithms and data structures
Shelves:
computer-science
When you want to read a good introductory book about algorithms and data structures the choice comes down to two books: Introduction to Algorithms, Second Edition and this one. I especially liked The Algorithm Design Manual because of the author's writing style, the "war stories" (that are some clever and practical applications of the data structures and algorithms the author tries to teach you) and the second half part of the book which is a sort of encyclopedia of problems.
I used the "introduc ...more
I used the "introduc ...more
Dec 18, 2011
Christian Brumm
rated it
it was amazing
·
review of another edition
Shelves:
cs-software
In comparison to "Introduction to Algorithms" (the other algorithm book I had significant exposure to) this one is faster to read, easier to digest and more tailored towards applications.
I found the "Hitchhiker's Guide to Algorithms" in the back to be extremely useful if you really find yourself tackling an algorithmic problem in practice.
The main part (maybe skipping/skimming down a few chapters) is a very good preparation for algorithm-heavy job interviews (e.g. Google, Facebook etc ...).
Very ...more
I found the "Hitchhiker's Guide to Algorithms" in the back to be extremely useful if you really find yourself tackling an algorithmic problem in practice.
The main part (maybe skipping/skimming down a few chapters) is a very good preparation for algorithm-heavy job interviews (e.g. Google, Facebook etc ...).
Very ...more
This book is a practical, example-driven book on computer science algorithms, which is very readable and has a wealth of ready-to-use examples. The tutorial material in the first half of the book covers the essentials: data structures such as lists, arrays, stacks, queues, binary trees, etc. The book spends a lot of time emphasizing the utility of graph algorithms and how to model various classes of problems with them, as well as lot of time on dynamic programming and backtracking/enumeration. A
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This is not an introductory book. You should have some previous knowledge of algorithms to enjoy it. The book builds a way of thinking towards solving algorithms problems, instead of just stating the algorithms and data structures in a mechanical way, but in many parts it is not very clear and you have to read a passage multiple times to understand what the author meant.
The book can be used as a reference that you can use to understand a specific topic.
The book can be used as a reference that you can use to understand a specific topic.
I can't think of an occasion when I'd recommend this over Intro to Algorithms (CLRS). It does a fraction of what CLRS does and worse in most cases. And in the rest of the cases, it does them exactly the same. There were some instances (graph algorithms) where the code in Skiena was taken straight out of CLRS. Not only did CLRS explain the algorithm better but it had the proofs to back it up.
Speaking of proofs, this is what I hated about Skiena. It has barely any proofs in comparison to CLRS. A l ...more
Speaking of proofs, this is what I hated about Skiena. It has barely any proofs in comparison to CLRS. A l ...more
Highly recommended for anyone interested in practical algorithm implementation.
A rare book on algorithms that is actually fun to read :)
Very good examples and explanations of algorithms that are commonly asked in interviews.
Dec 05, 2018
Joe
rated it
really liked it
·
review of another edition
Recommended to Joe by:
Fivebooks
The rare computer programming book that I finished start-to-finish.
The first half of the book tells you why some things take longer to compute than other things. This helps data scientists / statisticians / analysts who work with large amounts of data.
In the first half, the math and the computer code can get pretty heavy. But I found the text around it was written so you could skim the hard stuff, get the idea, and keep going.
The second half of the book is a reference. As Hadley Wickham said in ...more
The first half of the book tells you why some things take longer to compute than other things. This helps data scientists / statisticians / analysts who work with large amounts of data.
In the first half, the math and the computer code can get pretty heavy. But I found the text around it was written so you could skim the hard stuff, get the idea, and keep going.
The second half of the book is a reference. As Hadley Wickham said in ...more
One of the best Algorithmic Design books out there: not only does it approach every problem with the consideration of heuristic and through reasoning and demonstrations, but it also helps with writing simple code.
What makes this book better than most other books about the topic is the scrupulous definition of each term, and the absurdly clear explanation of every problem and heuristic that's presented throughout the volume.
Overall, i'd definitely suggest this book to anyone interested in algorit ...more
What makes this book better than most other books about the topic is the scrupulous definition of each term, and the absurdly clear explanation of every problem and heuristic that's presented throughout the volume.
Overall, i'd definitely suggest this book to anyone interested in algorit ...more
Holy crap, wish I'd found this book before I retired. I've been recommending Sedgwick's book for 30 years, this one is even better.
Something I really like is how he shows how useful graph theory can be. If you can turn your problem into a graph (and you'd be surprised how often you can) there are a lot of non-obvious algorithms that will beat the pants of any non-graphical algorithm. I got a B.A. in math, the most useful class I took was graph theory.
Something I really like is how he shows how useful graph theory can be. If you can turn your problem into a graph (and you'd be surprised how often you can) there are a lot of non-obvious algorithms that will beat the pants of any non-graphical algorithm. I got a B.A. in math, the most useful class I took was graph theory.
Skiena is an extremely likeable author! I loved his stories and sense of humor. I think I'd recommend this book over CLRS, although I could imagine a past version of myself being frustrated by the practical lack of detail.
Excellent Book but obviously not for beginners. You need to do refresher course in Algorithms or take one if you are graduating. You will become good problem solver and algorithmist after completing this text. Go for it if you want to challenge your algorithmic learning.
Not bad, but I preferred CLRS. Okasaki is miles more enjoyable than either of them, but of course has a different scope.
Rather good as a cover to cover read and as reference as well. It might get a bit too fast paced towards the end, but still loads of good information and ideas
Explanation is an art and Skeina is a master on it.
My favorite Algorithms book. I will always read and re-read it.
The best algorithm book I read, ever.
Algorithm books are usually not meant to be read fully as a novel, but used as a reference. Skiena's book is both. It focuses on real life practical examples. It even has some measure of good humor and memorable quotes (“It is amazing how often the reason you can't find a convincing explanation for something is because your conclusion is wrong.”). This makes you feel empowered about using algorithms to solve practical problems and feeling excited about software engineering in general. This book
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Il libro del professor Skiena è diviso in due parti.
La prima parte è teorica e tratta gli argomenti classici di un corso introduttivo sugli algoritmi: le nozioni di base sulla complessità, sulle strutture dati, gli algoritmi di ordinamento, gli algoritmi sui grafi, la programmazione dinamica, il backtracking, come trattare i problemi "intrattatabili".
In tutta la prima parte sono presenti le cosiddette "War Story": si tratta di paragrafi discorsivi che mostrano l'autore alle prese con problemi pr ...more
La prima parte è teorica e tratta gli argomenti classici di un corso introduttivo sugli algoritmi: le nozioni di base sulla complessità, sulle strutture dati, gli algoritmi di ordinamento, gli algoritmi sui grafi, la programmazione dinamica, il backtracking, come trattare i problemi "intrattatabili".
In tutta la prima parte sono presenti le cosiddette "War Story": si tratta di paragrafi discorsivi che mostrano l'autore alle prese con problemi pr ...more
This book is a great overview of the many families of important algorithms in computer science. The explanations and motivations are clear and engaging; I particularly liked the little "war stories" that accompanied each section, showing real-world applications of the algorithms being discussed and detailing the thought-process behind the matching of problem to algorithmic solution.
The only downside is the author's glib dismissal of the importance of parallel computing and the realities of hardw ...more
The only downside is the author's glib dismissal of the importance of parallel computing and the realities of hardw ...more
This book has served me well. It is quite readable and helped me stay on track when I found the CLRS "Introduction to Algorithms" book too formal and dry. Although its C code examples are rather archaic, they are still far nicer than the pseudo-code used in CLRS.
It's not as thorough as CLRS, with very little discussion of proofs. Also, it doesn't cover as many data structures or algorithms other than as brief mentions in the huge "Catalog of Algorithmic Problems" that takes up the second half of ...more
It's not as thorough as CLRS, with very little discussion of proofs. Also, it doesn't cover as many data structures or algorithms other than as brief mentions in the huge "Catalog of Algorithmic Problems" that takes up the second half of ...more
After I read this book, I heard that my co-workers use it as a source for interview questions. It's certainly more than that.
Skiena is an engaging writer. The beginning of the book covers algorithms -- such as sorting -- and techniques -- such as simulated annealing and dynamic programming. Then it discusses the importance of getting data structures correct because they influence which algorithms make sense. After a discussion of P vs NP complete vs NP hard (and why a polynomial time solution to ...more
Skiena is an engaging writer. The beginning of the book covers algorithms -- such as sorting -- and techniques -- such as simulated annealing and dynamic programming. Then it discusses the importance of getting data structures correct because they influence which algorithms make sense. After a discussion of P vs NP complete vs NP hard (and why a polynomial time solution to ...more
great practical guide, lots of fun to read on the subway. probably a better book to carry around in one's professional life than CLR, though it lacks some of the theoretical intensity of the Big White Book. i'm interviewing with Google and Amazon this week and picked it up to refresh myself on graph algorithms and strategies for NP-complete problems, and it delivered, with perhaps greater effect (and certainly less time) than rereading Algorithmic Graph Theory and The Theory of NP Completeness.
Great source of inspiration, it isn't as thorough as the Cormen/Rivest, but its strength lies in the second part of the book, with tons of problems explained and the most amazing bibliography.
From a practical point of view it is the best algorithms book I've ever seen, and probably a good starting point for every algorithmic problem you might encounter in your career; nonetheless, it's just a starting point, it gives you the right direction but then you'll have to search for more thorough source ...more
From a practical point of view it is the best algorithms book I've ever seen, and probably a good starting point for every algorithmic problem you might encounter in your career; nonetheless, it's just a starting point, it gives you the right direction but then you'll have to search for more thorough source ...more
This is the book that you would want to keep next to you for your major algorithm references. Not a typical text book on algorithm with "gory" mathematical details and also not a beginner's book. Friendly for those who are looking for practical applications of major data structures and algorithms. However I wish the book has more about tree data structures and it's algorithm. Nonetheless it is a good book to have at your disposal.
Algorithms
This is, hands down, the best introductory book to algorithms I have ever read. I've read "Intro to Algorithms" and "Computers and Intractability", and while those two are very good and for some applications better, for the novice algorist or person looking to refresh their knowledge on Data Structures, runtime growth, and popular problems with the algorithms that solve them - I don't think you can do any better than this book.
This is, hands down, the best introductory book to algorithms I have ever read. I've read "Intro to Algorithms" and "Computers and Intractability", and while those two are very good and for some applications better, for the novice algorist or person looking to refresh their knowledge on Data Structures, runtime growth, and popular problems with the algorithms that solve them - I don't think you can do any better than this book.
Its a good book, but I personally prefer "Algorithms, 4th Edition by Robert Sedgewick and Kevin Wayne".
I enjoyed reading the first part involving his "war stories". However, I would have loved to see examples in C++ or Java or any other modern programming language instead of C.
The second part ""Hitchhiker's Guide to Algorithms" is more for reference that you can refer to if you are stuck with a problem and want to know what to do.
I enjoyed reading the first part involving his "war stories". However, I would have loved to see examples in C++ or Java or any other modern programming language instead of C.
The second part ""Hitchhiker's Guide to Algorithms" is more for reference that you can refer to if you are stuck with a problem and want to know what to do.
Thie book is presented in two parts.
The first is a series of war stories and describes the approaches to problem solving. I found this the most useful part, giving you an insight into how to turn an concrete problem into an abstract problem that maps to an algorithm. The second is a catalogue of various algorithms according to category.
The content is very accessible and less dry than other algorithm books such as CLRS.
The first is a series of war stories and describes the approaches to problem solving. I found this the most useful part, giving you an insight into how to turn an concrete problem into an abstract problem that maps to an algorithm. The second is a catalogue of various algorithms according to category.
The content is very accessible and less dry than other algorithm books such as CLRS.
This book made studying for some technical interviews easy, saving tons if time in searching for different resources on the web, while also giving insights that are uncommon to be found in most algo books.
The war stories that pepper the book make it a fun, cover-to-cover read, while the cookbook at the end makes it a great reference book.
The war stories that pepper the book make it a fun, cover-to-cover read, while the cookbook at the end makes it a great reference book.
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