Introduction to Algorithms, Second Edition

Written by an MIT professor, this book covers ALL categories of computer algorithms. It is a somewhat challenging textbook for a first course in computer algorithms, but students can keep the book past graduation, and use it as a reference book while they work as professional software engineers.

Giving this book a bad review because: a) you had a bad instructor for the course b) you find the material difficult c) you can't understand pseudo-code are not what I would call constructive or worthwhile critiques of the text of this excellent book. PLEASE society, PLEASE understand that some topics you have to actually WORK at understanding. It won't be spoon fed to you. It seems moreso with Computer Science majors than other majors (I'm an electrical engineer undergrad, comp sci grad student) that they whine and whine and whine about the math or about it being difficult to actually have to work to understand something. Oh my GOODNESS!!!! It's hard? Well, BLAME THE BOOK. Rant over. This book is amazing. It's the bible of algorithms and, to some extent, data structures. If you're not aforementioned whiners, feel free to buy this book, work hard, and learn a lot! There's not a better book out there in my experience.

This is a book that was recommended to me by an actual HR rep at a top technology company. Despite the fact that I was pursuing a Program Manager position, she said that I'd still need to prep up a bit for Data Structures and Algorithms. Needless to say, I didn't do well on the interview, but the topics discussed throughout the book gave me an excellent introduction to the topic, and now I think that knowledge of algorithms is absolutely essential to being a good programmer. This book doesn't really assume any knowledge about the topic, so it could be a great way for you to get your feet wet on the topic.

Overall this is a good book and well worth every cent. The material is covered better than most data structure text books. It also avoids using recursion in situations when its not needed. For example, the texts chapter on red-black trees is probably the best I've seen. It explains key concepts while building on previous knowledge with notes to where the previous material was covered. The red-black tree is explained without using recursion, because the authors were smart enough to have realized the general reader cares about creating practical data structures without any or much lost in performance. Cormen et al does this well indeed. Each algorithm is laid out in pseudo-code that can easily be adapted to code in any language. One of my dissatisfactions was with the presentation of the pseudocode in that the indentation was done in a strange manner. This made the scope of the blocks of logic in certain algorithms confusing. Furthermore, the binding of the book is quite fragile and would most likely be broken with casual use as a textbook in college. However, I suspect the author did this to lower the price for college students and I thank him for that. In conclusion, this is near perfect book and is the reason why I give it four stars instead of five. If you are seeking a good data structure or algorithm textbook, then you cannot go wrong with Introduction to Algorithms.

Great for uni and onward, a bit old and is all pseudo code but still great

This is a super great book to start learning all about algorithms. It is very straight forward and easy to understand. If you don't understand any terms or even some of the math that is shown, the appendix and sections in the back will tell you everything you need to know. it covers every topic thoroughly and tells you exactly how and why each section relates to the chapter and why it's important. Essentially, this is THE book to get if you want to study algorithms, even a little.

First, the good part: this book is an intellectual and academic masterpiece. It would be great for people doing algorithm or other Computer Science research. It's an amazing synthesis of much of the core of a Computer Science degree with Discrete Math and Probability. Oddly, it's more like a math book than a CS book. Now, the not so good part: for implementers (i.e., programmers), this book is not all that useful. The biggest technical negative is that, for the most part, the authors ignore memory hierarchies and treat everything as if it were running on a computer with infinite cache memory and having everything already loaded there. Granted, the authors spend a huge chunk of time teaching the readers how to do (and prove) cost (or efficiency) analysis on algorithms. So, readers should be able to figure out actual, real-world efficiencies on their own (although there's nothing in this book to illustrate how to modify the analysis to do that). But, since memory hierarchies drastically change the relative efficiencies of algorithms, they should be considered in the original algorithmic analysis and ranking. From a methodology point of view, another problem is that the authors assume the readers have full knowledge of the algorithms covered in the book. In general, they don't even try to teach the actual algorithms, how they came about, the reasoning behind them, or any method of thought for coming up with other, similar, algorithms. Instead, the authors merely focus on proving the correctness and cost of the pre-existing algorithms. It's like the authors present a beautiful, theoretical, shiny structure sparkling and spinning in the ether. They then explain what parts make up this structure, how they're put together, and how long it takes to use such a structure. But, what would be far more useful is if the authors started from the more common position where someone has a problem and a big pile of parts. They need to know how to determine the best thing to make from all those parts to fix the problem, and how to put it together in the most efficient way. Essentially, it's the difference between a reference book and a teaching book. On the level of irritations, the authors leave a LOT of core stuff as exercises for the student. This is bad enough on its own (and is one of my pet peeves in the math world). However, making this even worse is the fact that NONE of the exercises are answered. So, firstly, that makes these exercises useless to self-studyers (i.e., me). And, secondly, that makes the "proof is left as an exercise to the student" core parts of the book entirely inaccesible to self-studyers. I can't emphasize enough that academically and intellectually, the scope and depth of this book is amazing. If I were someone doing pure research in computer science algorithms, I'd rate it at 5 stars out of 5. But, as a lowly nouveaux-programmer trying to improve my mind, the best I can give it is an OK 3 stars out of 5.

このでかさは二つの意味の武器を持つ。まず、1000ページを超える厚さで重いので物理的な武器にもなれば、これを読めばかなりアルゴリズムに関して幅広く知ることができると言う意味での武器もある。さて、そのような冗談はおいてこの本を評価したいと思う。 この教科書はアルゴリズムとデータ構造における世界水準の入門書であると考えていい。（というか多くの人はそう考えている）当然だが、「Introduction to ALGORITHMS」であるから、プログラミング言語と結びつけてはおらず擬似コードで話は進められる。そこらあたりにあるアルゴリズムとデータ構造の本よりかは古本でもこの本を買ってしまえばいい。おそらく大学の講義（15週くらい）では絶対に終わらない内容がズラーと並んでいることから、アルゴリズムを専攻したい人、研究に使う人には手放せない一冊になることには違いない。 何を詳しく取り上げると言うのも題材がそもそも多すぎるので、述べないがアルゴリズムとは何かと言うのを10ページにわたりわりとしっかりかかれている。どうしても、大学で使っているアルゴリズムとデータ構造の教科書は難しいし、アルゴリズムは何に使われているのかなどが書かれておらず、アルゴリズムを初めて学ぶ人には敷居が高かった。そういう意味でこの本をサプリ的に買った。これを読めばアルゴリズムは面白いと必ず思わせてくれる。 これだけ長々と書いたが、要するに「世界水準」ということから読んでわかりにくいと言うことはまずないだろうし、ちゃんと理解できる。

This book covers my whole university course for all 3 years.

Best deal for this textbook. Well, it's a textbook, so there is not much use for it unless you are taking corresponding course. It does contain interesting algorithmic theories but I doubt anyone would actually use this as a "casual read"...

Todo lo que quieres saber para comenzar en el mundo de los algoritmos está aquí. Como en cualquier otra ciencia, no todo el conocimiento puede estar en un sólo libro, pero tras acabar este tendrás un buen nivel y competencia en diversos campos de la algoritmia. No obstante es un libro denso, poco divulgativo (no se lee por placer, se lee para aprender a hacer algo concreto, algo que en general es dificil), y que requiere tiempo por la cantidad de conceptos y datos que aporta en cada una de sus páginas. Un libro para tomárselo con calma, o para consultar y repasar conceptos cuando sea necesario. Ideal para gente con experiencia en programación, matemáticas o, al menos, algún trasfondo en materias lógicas. No recomendado para una persona que esté aprendiendo en frío o que nunca haya tenido una aproximación, al menos, a la programación.

Great book with a good condition. I`m satisfied.