Customer Reviews

Fundamentals of Algorithmics

5 star:		(2)
4 star:		(4)
3 star:		(0)
2 star:		(2)
1 star:		(6)

 

 

This book is written in a simple style: algoritm class description, related proofs, examples, variations and exemples. Because of this clean approach, you can basically read it in a couple days if you have the necessary background knowledge, and in a couple weeks if not. I strongly recommend this book to everyone who are calling themselves "programers", either graduated or not, it will teach/remind them what are the elegant fundamental algorithmic approches to common problems; it's seems that today's software could use a bit of this elegance. As for all the negative reviews, I'm astonished. I own several books on the subject, and I find this one the easiest to read, no question. It must be some sort of personal vendetta against the author, a failed undegraduate course with this book as teaching material, or some other personal reason; that's probably why this/these person(s) whish(es) to remain anonymous.

One of the few books organising algorithms around design techniques instead of application areas (see "Algorithms" from Sedgevick). Though both approachs have pros and cons, I've found the former most convenient for people learning to design algorithms. Many problems admit several solutions depending on the design tecnique involved. This fact is emphasized by the authors.

The book is self-contained, plainly written, so that an undergraduate can read it after taking a prerequisite course on programming.

It's also mathematically rigorous, while mantaining simplicity. This allows analysis of algorithms to be really "analytic" (no more guessing the solution to a recurrence relation).

One main drawback (certainly usual) is the lack of excercise solutions.

This is a good book - far better than an average rating of 2 stars
would suggest. However, i think a big reason for such a rating is
that it's supposed to be an introductory textbook (as claimed by the
authors in the preface), and from that point of view, it leaves much
to be desired.

The presentation is such that it can be difficult for first-timers to
follow, and many topics are simply absent, e.g. network flows.

On the other hand, those already familiar with the material will find
it quite readable and handy as a reference or for brushing up.

The authors choose to present algorithms from a design point of view,
ie greedy approach, divide-and-conquer, bactracking, dynamic programming
etc instead of the traditional way of presenting algorithms for solving
a class of problems, e.g searching, sorting, graph algorithms and so on.

While this is good for those who're already familiar with the traditional
approach and also offers a unified view of problem-solving strategies in
Algorithmics, it is decidedly easier for the beginning student to have (e.g)
all sorting algorithms in one place than to discover that they're scattered
across different chapters.

All algorithms are presented in pseudocode, and are thus have no
programming language dependencies. A healthy number of solved examples
have been provided, and unsolved problems are numerous.

In summary, i think this is quite a good book for practitioners, researchers
and those doing an advanced course in Algorithms, whereas it may not be
suitable for an introductory course (except, perhaps, as a supplement).

I don't agree with the other reviews. This book is a serious one and it is a "smooth" version of "Algorithms: Theory and Practice" from the same authors, which has a 5 stars rate. The book don't teach how to program, but the main kind of techniques in algorithm design (Greedy, Divide and Conquer and Dynamic Programing techniques, and others like Backtracking, Probabilistic Algorithms, etc.). I teach a course of Algorithm Design with this book (having the Sedgewick and Cormen books like additional very good references) and I think that it is a very instructive course on algorithmics (but NOT in programming, of course).

I didn't like the organization of the book. It starts with page after page of the mathematics used to analyze algorithms. This could be shortened considerably. Then an analysis of some multiplication algorithms which are poorly explained. Most explanations are long winded and the pseudocode isn't that great. The one section that is o.k. is on probabilistic algorithms, including prime number generation and a little cryptology. In general there are many better books of this kind (Sedgewick, Baase, Corman, Aho, etc.)so that one wonders why this book is even out there. Maybe the author feels that organizing the book based on algorithmic technique as opposed to algorithmic function will help the reader. Sometimes it's just annoying since things like sorting are spread all over the book depending on the techniques used for the sort. Choose another book for algorithms.

I took the class IFT2121 given by Gilles Brassard, and thanks that we had book which is so well done and complete.

People misunderstand sometime the nature of this book. This book is not about providing algorithm recipe but to teach you the methods used to analyze the performance of algorithms.

Gilles Brassard is an outsanding teacher, he is very sharp, he knows his stuff inside out, and his book is a master piece!

Wow...I don't understand how this book can be used in an introductory course to algortithm analysis. I can see where readers with a great deal of mathematical skill would like this book, because that is the only way you are going to understand any of it. There are too many instances where the authors gloss over their explanations, saying that the answer is "Easily derived". If you have a Ph.D in Mathematics and an entry level skill of programming you might like this book. Otherwise, avoid it all cost.

I had the misfortune of enduring this book during a graduate level course in algorithm analysis. Bad writing and incomplete explanations make the book a bad choice to learn this complex topic. Most of the itricate and particularly tricky parts of various proofs are left as "exercise to the reader"! Why bother when there are so many better ones to choose from?

I got this book for an Algorithm class at my school, and found it to be a bit tough to read, it was very complex, and from the beginning started off with advance notation and highly mathematic language. The book does not provide nearly enough examples, to help with assignments (or problems from its review), and forced me to have to turn to the internet for easier to follow guidance. The book offers examples and plenty of proofs, which make this book nice for reference for proving a fact or referencing a paper, however, it is not very practical for use in the classroom, since it does not offer enough examples to follow to learn how to complete assignments.

In the end this book offers great proofs and highly involved algorithms in pseudocode and mathematical notation, which makes this book great for reference and writing papers, however, it lacks in helping in the classroom for assignments and other items where an easy to follow example would helpful. However, for any one interested in Computer Science, I would recommend this book, for reference for algorithms, and their worst/best case analysis.

The reason I dislike this book is that it is written in a conversational style, which is very hard to follow. Being a beginner at this, it would be much more helpful if things were separated and clearly emphasized step by step. This book makes it difficult because all proofs are written into a big block of a paragraph. I normally have taken an hour or so to decode a paragraph so that I can say "Oh! That's what he meant." The content is good- layout is bad.