Introduction to Algorithms, 3rd Edition (Mit Press): Cormen, Thomas H, Leiserson, Charles E, Rivest, Ronald L, Stein, Clifford: 9780262033848: Amazon.com: Books

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.

"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 am a math major who has taken a few cs courses from the cs department at my university. Up until reading this book cs has always been a bit of a mystery to me. I have heard a million and one time how cs is based on mathematics but aside from understanding the idea of traversing through arrays as you would the indexes of a sequence, I have never really seen the connection between the two subjects. This book does an amazing job of demonstrating the mathematical basis of cs. From the very beginning when the authors deconstruct the for-loop used in a insert-sort into a variation on mathematical induction the lines between the two subjects are made crystal clear.I would agree that a pretty solid understanding of mathematics is required for this book, and I can see why someone coming from a typical undergraduate education in cs would find it difficult and intimidating to tackle this book. It definitely does not teach you how to program or the basics of object oriented design as it proceeds to teach you about structure and design of algorithms. I can also understand why someone hoping to simply get a job as a "programmer" or "software engineer" would not necessarily be well served by this book. The authors are very upfront on this note though, and specifically warn prospective students that they are not going to teach them how to "code" solutions to common cs problems. What they are going to teach them is the fundamentals of algorithm analysis and design. How valuable prospective students find this approach is going to depend entirely on what exactly they hope to do with their understanding of computer science. If you want to learn how to code and be paid to be a developer (not a bad line of work by any stretch of the imagination) you might want to look else where.For someone coming from a mathematics background though (whether it's an applied field such as statistics or numerical analysis or a pure field like abstract algebra or analysis) this is an excellent introduction to the field of computer science. If you are coming from a math background the analysis and structure of algorithms as presented in this book will instantly click. For me personally I loved the fact that the underlining mathematical basis of cs did not get lost in details of coding or working within certain developmental environments like Eclipse. Again, probably not an ideal choice for someone looking to learn this particular subjects, but definitely a good choice for math majors (or prospective cs grad students).