Customer Reviews

Algorithms: Design Techniques and Analysis (Lecture Notes Series on Computing)

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

 

 

The book represents a well written, consistent and easy to follow view on the area of algorithm analysis. It gives an excellent overview of various mathematical and computer science areas, including but not limited to combinatorial geometry, NP-problems, complexity theory, graph theory, algorithm analysis, dynamic programming and even computational geometry.

Most of the chapters are intended for a senior level undergraduate and graduate student, but some (such as part 4 devoted to complexity problems) are more suitable for "mature" audience and require some preliminary knowledge in the area.

I found chapters on sorting, data structures, recursion and functional programming well written and structured, and examples to be practical as well as informative.

Sections on amortized analysis, randomized algorithms, approximation algorithms and iteration improvement deal with current directions in the algorithmic research and provide an excellent overview of the "state-of-the-art" in these areas. I also enjoyed reading through the section on greedy algorithms (shortest path and minimum spanning tree problems).

Section on computational complexity and analysis of the relationship between complexity classes seems to be a bit complicated, those who are interested in this area should probably do some preliminary reading.

The last section on computational geometry (my area of expertise) and applications of Voronoi diagrams could be extended, but even in the current state it givs a pretty good idea of what computational geometry is all about.

Overall, I give to this book a "5 star" review and recommend it for anyone who is seriously interested in learning exactly how algorithm design and analysis work. I thoroughly enjoyed reading this book and can only wish that author would write more books like that in the future!

This is a great book overall, but I give it 4 stars as it lacks the mathematical explanations that I personally was looking for. I am graduate student in Computer Science and a E-Commerce Consultant by profession. This book is more detailed than the Sedweick (I can't spell his name) in the sense that it has some more of a mathematical approach. It lacks the level of explanation that the Sedweick book provided. It has some math, but overlooks some steps thus targeting someone with a pretty solid math background, not someone with sophomore level undergraduate math background.

Overall.. if you're a student taking an algorithms or advanced algorithms class (especially a graduate class), you might want to invest in this book.

I have studied both undergrad and grad algorithm courses from this book at KFUPM. For a beginner, the author provides a moderate level of mathematical analysis which helps in building a solid foundation, but avoids minor details that may obscure the overall grasp of the subject. The Exercise sets at the end of each chapter vary from easy to challenging....

I have been using this book as a second reference in my Algorithm
Engineering class during the whole semester. I found it extremely useful for its nice structure, content and diversity of subjects treated, especially the ones in computational geometry such as Geometric Sweeping and Voronoi diagrams, for instance. I believe this book should be useful to any student taking algorithms class for its structureness, clearness, and completeness.