3rd Edition (The MIT Press) - Introduction to Algorithms

"An Introduction to Algorithms", a big book, is worthwhile the time. But, I must admit to being 1/4 through iTunes U MIT course "6-046J: Introduction to Algorithms". The textbook feedback is seriously helpful, but I could not manage without the lectures. For what it is worth, my life's course has been the trash-heap quality programming must immediately face, and I've started the course to try to put into some perspective what my efforts have meant over the years, if now largely obsolete. The number of relevant insights have been affirming- I've played in a busy patch and many of the topics covered (to date) have indeed been of real interest ... if only I had known a bit more at the time about what was in fact a lot of blundering around. And, there are some gems. My 1968 Graduate Diploma included some list management, for which which "move to front- MTF" can only be described as spookily revealing of what was going on all those years ago. Modern methods are scary. Such a simple process being within 50% of the efficiency (25% as described in the applicable lecture with reference to the optimising original paper) of what God could manage is humblingly inspiring. Buy the book if you intend to devote a slab of life to getting better acquainted with modern applied logic, but remember the lectures.

I'll have to agree with my computer science professor: this is one of the best books on algorithms out there. It's extremely comprehensive and covers virtually all commonly known programming algorithms. The book does not waste pages; it goes into the pros, cons, and run-times of each major algorithm with appropriate diagrams and explanations. Each main section of the book is independent of each other; my professor made a habit of using the book out of order. The homework questions at the back of each section promotes critical thought - they weren't easy at all.

This textbook isn't just a textbook for an algorithms class. No matter what the project, if you need details on any sort of data structure or algorithm, this book has details on it. It is very theoretical, but extremely comprehensive. Whether this book is required, recommended, or not even suggested at all, I cannot emphasize how helpful it will be. It is a textbook that will outlive the course by a very long time.

The book excels in giving bloated explanation for very old materials while succeeding to obfuscate even the most basic ideas and algorithms. While some algorithms covered with details, others, not less important, are marginalized to footnotes and exercises. While the book is exceedingly thick, it omits important current topics such as Suffix Trees and Ukkonen's algorithm. Seemed that that main goal of the third edition was to increase the page count while hardly adding new materials or improving existing one. The only justification to purchase the book is the lack of others more current ones.

wont work with cloud reader or android. does work with pc kindle app.
An excellent book if you're _serious_ about algorithms but the "kindleization" is very poor compared to other classics like Hennessy & Patterson

Was this expensive? Yes. Was it overpriced? No.

My algorithms class was hard (what algorithms class isn't), and I'm not always an ideal student. I had a lot of trouble attending lectures and keeping up with the lecture recordings posted online. Still, I managed to get a 90/100 on my first exam. Not bad, right? I mean, even if it's only barely an A, it was still a high grade right? WRONG! It was an amazing grade! Turns out the class average was 45/100, and I had the highest grade in the class.

Pretty crazy, right? WRONG! Exam 2 was where things got crazy. Maybe I was getting over confident, or maybe I was just really lazy, but I didn't watch or attend a single lecture between Exam 1 and Exam 2. The class average was a decent 83/108 this time, but my grade was 108/108. A perfect score without watching a single lecture. So what happened?

I wasn't kidding about being a non-ideal student. I had a 2.9 GPA in undergrad, so I didn't manage this through sheer brain power. What I *did* do was a single homework assignment from this book before every test. After attending office hours before exam 2, I found out that almost everyone else was finding the answers online and copying them for good homework grades. These homework assignments were hard, taking around 8 hours to complete, and I still missed a lot of them, but it still worked.

It is no exaggeration to say that the homework problems in this book got me an A in Analysis of Algorithms.

This book is a great resource and working through it has definitely improved my skills in this area. It doesn't always go through things in the easiest manner to digest, but it seems to be one of the better textbooks out there. If you want to understand algorithms, read this book.

The perfect book for a software engineer who's been out of school for many years to review a wide range of algorithmic topics. This reference greatly helped me land a job offer from a major software company.

The algorithm bible. If you want to buy just one good text on the subject, start with this one. It was recommended to me by a professor at a University in Tennessee as the best all-around text on algorithms. And, they were right. Meets all my expectations.

This book is excellent! It's the most widely used textbook for algorithms courses. It presents the concepts and examples in a clear manner, and the exercises at the end of each chapter really make you think and help you understand the subject.

Algorithms is the type of subject that can make you put your hand on your head in frustration due to the technical nature of the subject. This book does a terrific job of demystifying topics and giving you a clear and concise notion of the fundamentals which make the algorithm work. In turn, the authors have gotten me to love learning about algorithms. Every chapter is a new challenge, and the authors are there to help guide you the whole way.

Cormen's Algorithms book is highly regarded as one of the best algorithms book out there, and though I have no experience with any other algorithms texts, it's fairly obvious to me now why that is true. Cormen's book is mostly well-organized, is easily readable (especially with all the great pictures and examples!), and is best used as a workbook text. Pretty much all of the chapters rely on chapters previous to some degree, and the exercises especially reflect this behavior as many of them require you to you optimization learned in previous chapters to modify current algorithms. Overall, I have very few complaints, and this text has been one of my favorites throughout college.

My first complaint is that the text begins by throwing you in to the analysis of insertion sort before defining any notation or mathematics used to analyze the algorithm. While I understand that the idea is to introduce you to what algorithm analysis really is, the chapter felt more confusing than helpful. I would much rather the book started with background information first.

Secondly, the mathematical chapters are very brief and vague. Chapters 4 and 5 are particularly bad due to the lack of depth, explanation, and clarity. The examples are far from satisfactory, particularly those regarding probability and recurrences. While these chapters had excellent problem sets, I needed an external source to help me deal with cases not covered in the text. One example of a topic I had trouble with was solving for the number of levels a recurrence tree has. The book only presents trivial examples of this while the problem sets ask for significantly more work. One or two worked out examples, even if they were only included in the selected answers, would have been very helpful.

The last issue that I had with the book was the lack of explanation given in the analysis of specific algorithms. For example, the runtime analysis of Kruskal's minimum spanning tree algorithm felt far from intuitive. The author does not take enough time to explain where some analysis techniques came from and why they were used. Though many of the algorithms are discussed in enough detail, there are several more advanced algorithms which feel like they were thrown into the text without enough care.

Despite all these issues I've been very pleased with my purchase and the time I've invested in it. I would recommend the book to anyone with interest in algorithms. While some knowledge of basic mathematical analysis and probability theory would be helpful, it's pretty easy to get by without either of these. Though the explanation of some of the more technical parts of the book is lacking, the authors do a great job of translating complicated psuedo-code and notational necessities into something which is very easy to understand

Studying this book will help you land a job faster and for better pay. (It will improve your day to day coding, too.) Go in ready for Dijkstra's algorithm, and you are ready for any interview question.

I bought this book as per [...], and prepped as hard as I could (while holding a job) for a little over a month before a Google interview. I read it and did exercises in just about every spare moment.

They rejected me, but when my whole department got the ax soon after, that prep helped me end up with two different offers, both significantly better than the old job.

This textbook is a mixed bag. Some sections are well written and explain concepts properly, others simply throw a mathematical proof at you with no explanation as to what the algorithm is even supposed to do. It comes across as being written by a mathematician who hasn't touched a computer in the last 30 years, if ever.

Not a great textbook, some of the assignments were not thoroughly explained in the reading and relies heavily on your own extracurricular self study. Reading helped clarify some lecture materials but again, not a good book to supplant algorithm lectures. Secondhand copy was cheap though and was the alternative to scanning hundreds of pages from library copy.

The biggest difference between the international edition and the normal edition is how cheap it is, and man, my copy looked cheap. It looks like the graphics were printed with a low quality printer, after being a copy of a copy. The pages are misaligned, and the paper has a purplish tint. I got it 'new', but, but the back binding was crinkled a bit, and the edge looked discolored.

But it was a lot cheaper than the standard edition.