Introduction to Algorithms, fourth edition 4th Edition

I hate this book with the kind of deep hatred reserved for the kid who beat me up and took my lunch money back in grade school, because that is what this book reminds me of - a big bully slapping me around with all of its math notation and theory.If you are the kind of person who loves math notation, can implicitly understand "abuses" of notation, likes to write proofs in your sleep, then this is your book. Mere mortals who love programming and looking to get a better understanding of algorithms should avoid this book at all cost - it's a lot of money to pay for something that'll wind up on the bookshelf.However, I'm going to give this book a good rating.Hey, just because I don't want to spend my days obsessing about logarithms, recurrences, recursion trees, and theorems doesn't mean the content of this book isn't great.

This is an extremely high quality formal academic textbook on the subject of algorithms in computer science. This book likely gets assigned in many upper division or graduate level classes on the subject. For example, it has formal academic proofs of all of its claims about algorithms up front, and it is filled with exercises that are clearly intended to be completed by students. This is a formal and rigorous high level academic textbook, really serious stuff.The pseudo code is excellent, top notch, it makes even very complex algorithms readable. The pseudo code is close-ish to python in style, but the discussion of the algorithms more broadly is clearly written by people coming from a background in C/C++ since they reference pointers frequently during their explanations. The pseudo code is good enough that it could likely be used as is.The book I got was clearly freshly printed, it smelled as though the ink had just dried and one of the pages still needed to be separated at the bottom from another. So if you buy new, you might get a book that has just been printed, which is pretty cool. The printing (at least the hard cover) is very high quality, full color, glossy pages. There are some minor printing mistakes, but this is like a 1000+ page book, so the fact that 99% of it is perfect is pretty awesome.This covers virtually every common algorithm, and even includes mention and brief discussion of rare algorithms and variations of common algorithms. It's 1000+ pages, and I get the feeling that they packed in as much as they possibly could.I would love if they would release a second volume because they just didn't have room here to discuss everything. Like they mention a ton of variations of algorithms that they just don't have the time to explore. For example, I'd love to have a whole section dedicated to self balancing binary trees. They cover the most common self balancing binary tree algorithms, but they briefly mention and discuss at least 5-10 other related algorithms that I would love to see covered in depth.Likewise, I would love for a second volume to cover computational geometry, which is absent from this book. I totally get why they didn't include it, it's a whole field in and of itself, and this book is already 1000+ pages, and this book covers almost literally every other major algorithm and problem. That's why I hold out hope, not for a revised edition, but for a second volume that covers the stuff that this one didn't have time for.This book is a formal academic textbook. It's not an intro level text. You need to know your stuff before reading it. It doesn't try to be particularly easy to read, but nor does make the subjects seem overly complex. It's just a rigorous academic look at algorithms, like you'd expect in an upper level college course. Could it be written in a simpler style? Sure, but I feel like the market for this book is classrooms and academics, that kind of thing. It's still very readable as long as you know your stuff, just don't go in expecting intro level material. This is the opposite of intro level.If you are a software engineer, you pretty much owe it to yourself to own this book. This is the definitive textbook on the subject of algorithms. I really, really hope they release a second volume that covers all the algorithms that they only mention in this work. This work is very comprehensive, don't get me wrong. It covers pretty much every major algorithm that you'd want to know, with the obvious exception of computational geometry. It even covers the NP-Hard problems, it really is comprehensive. I just want all the more obscure algorithms too!Publishers and authors if you're listening, please release a second volume of this awesome book that covers everything you couldn't fit in this one!

New perfect !

I'm taking a computer algorithms class from a professor who actually wrote a book on algorithms. It's tough and I'm super confused. I got this Intro to Algorithms textbook to help explain what the professor thinks is obvious. This book has been really helpful. The book is huge and it covers a lot but it doesn't assume you already know the material the way a lot of other algorithm textbooks do. It explains complex topics very well and is a great book for those of us CS majors who don't immediately understand algorithms. I recommend this book even if you don't have to get it just as a reference for computer science majors. Understanding algorithms is critical for computer science jobs, if just to get past the interview stage and get a job, so I'm glad to have this book as a reference.

My experience with this book suggests that the mathematician Niels Abel was right when he counseled to ”Learn from the masters, not the pupils.”Where this book’s material overlaps with Knuth’s “The Art of Computer Programming”, the latter repeatedly shows itself superior. For example, in explaining binary trees, Knuth discusses at length what they are, how they differ from general trees, how they can represent general trees, how one can traverse them without recursion (preorder vs. inorder vs. postorder), and how one can tweak them for various gains in performance. CLRS just barely (or doesn’t) touch on these fundamental topics. Which raises the question who exactly this book is for — the introduction suggests it is for new-ish students, yet here they are expecting said students to intuit what Knuth dedicates multiple chapters to in TAOCP.And the rest of the book, or the parts I’ve read so far anyway, seem like that. Spotty exposition, leaving readers to scratch their heads over what are really the authors’ failures to properly introduce and expound on a subject in a nice and coherent way. Written by people who profess to understand what they write about, but who evidently lack the style and grace of a true master.