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Rating: 
Summary: An excellent self-study guide
Review: The text conists of of 40 'lectures' or chapters, each about 4-5 pages, 10 moderately difficult 'homeworks', each about 3-4 problems and one set of 29 miscellaneous exercises. Solutions to both the homeworks and miscellaneous exercises are provided. The text is based on the notes used by the author at Cornell in a one-semester graduate course.Each lecture is (largely) self-contained and brief. Being clearly written and concise makes it an excellent choice for those interested in self-study. The homeworks are the key to understanding the material. I would suggest trying for atleast a day before looking up the solutions. For more comprehensive treatment of the topics dicussed in the book see "The design and analysis of computer algorithms" (Aho, Hopcroft and Ullman) and "Computers and Intractability" (Garey and Johnson).
Rating: 
Summary: covers a lot of topics, sometimes difficult to follow
Review: This book covers a lot of interesting topics and is very up-to-date with current research results in the field. Its main drawback is that it has few examples. It is also at times hard to follow, unless the reader is already somehow familiar with the material.
Rating:
Summary: covers a lot of topics, sometimes difficult to follow
Review: This book is basically a set of lecture notes used by Prof. Kozen at Cornell, plus some practise 'homework' exercises. As such, it isn't really a textbook, and can't be used as the only book for a course in the design and analysis of algorithms - for that, you'll need the books by Aho et al, or Cormen et al. (Knuth's books, of course are great for the topics they cover; and while on the book by Cormen et al, there's a second edition now, since September 2001). However,this is an excellent self-study supplement. There are 40 lectures, each being a concise, self-contained discussion on a chosen topic. Thus, you get a condensed presentation of the important points, along with invaluable insights from Prof. Kozen. Another feature which makes this a great option for self-study/rapid review is that each chapter ends with 'homeworks', for which answers have been provided. There's a set of miscellaneous exercises as well. It is important to realize that this is a graduate text, for those who are already familiar with data structures and algorithms. This is not an introductory text by any means, and would ill serve that purpose.
The author presumes a fairly strong background in basic data structures and algorithms as well as mathematics on the part of the reader, without which it may be very difficult to follow the presentation.
All in all, if you're doing a graduate course in the design and analysis of algorithms, then this is a superb choice for self-study, practising problem-solving and rapid review of already familiar topics.
Rating:
Summary: Excellent supplementary text for a graduate course
Review: This book is basically a set of lecture notes used by Prof. Kozen at Cornell, plus some practise 'homework' exercises. As such, it isn't really a textbook, and can't be used as the only book for a course in the design and analysis of algorithms - for that, you'll need the books by Aho et al, or Cormen et al. (Knuth's books, of course are great for the topics they cover; and while on the book by Cormen et al, there's a second edition now, since September 2001). However,this is an excellent self-study supplement. There are 40 lectures, each being a concise, self-contained discussion on a chosen topic. Thus, you get a condensed presentation of the important points, along with invaluable insights from Prof. Kozen. Another feature which makes this a great option for self-study/rapid review is that each chapter ends with 'homeworks', for which answers have been provided. There's a set of miscellaneous exercises as well. It is important to realize that this is a graduate text, for those who are already familiar with data structures and algorithms. This is not an introductory text by any means, and would ill serve that purpose.
The author presumes a fairly strong background in basic data structures and algorithms as well as mathematics on the part of the reader, without which it may be very difficult to follow the presentation.
All in all, if you're doing a graduate course in the design and analysis of algorithms, then this is a superb choice for self-study, practising problem-solving and rapid review of already familiar topics.
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