The book is about algorithms and data structures in Java, and not about learning to program. My review will contrast this book with Sedgewick's 25+year old "Algorithms in C++" in my shelf. The new algorithms book is such a vast improvement over the old C++ book that I hardly recognize it any more. The new Algorithms has two authors. The authors are using a sub-set of the Java OO features (unlike the C++ version, which used none). While I may not agree in detail with some choices, I can understand, because they explained their coding standards well, and why they limit features. The algorithms are updated to the basic algorithms a student these days needs to have heard of, which includes new material like tries. I was fascinated to see a regular expression evaluation automaton in code, with explanations. Some more esoteric material from the C++ book (for instance, Voronoi diagrams) is left for specialized books. At a few places in the book, the impact of algorithms and data structures is illustrated giving real-world examples. And I have yet to read chapter 6.
But what really impressed me was the code. This book shows the fundamental data structures and algorithms in just a few lines of beautiful and well-thought code. Sure, any nit-picker may find quibbles, but most choices are understandable from a didactic and printing perspective. This code is so much better than any in the old C++ book. The authors preferred clarity, yet the code is still concise. The authors are clear about feature creep, and limit their code to what is needed and no more, though some extensions are part of the exercises. I am reminded of the Einstein paraphrase "As simple as possible, but no simpler".
More complex data structures and algorithms need multiple code boxes, which are all explained in detail, with the box appearing close to the explanation. Some readers may take issue with the density of information in examples, but I find it advantageous to have all information close-by rather than spread out. I prefer to pore over their dense examples than having to flip pages.
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Popular Highlights in this book
The primary purpose of static methods is to implement functions; the primary purpose of non-static (instance) methods is to implement data-type operations.Highlighted by 244 Kindle readers- An abstract data type (ADT) is a data type whose representation is hidden from the client.Highlighted by 225 Kindle readers
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From the Publisher
Distinctive Features
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AlgorithmsDescriptions of algorithms are based on complete implementations and on a discussion of the operations of these programs on a consistent set of examples. Instead of presenting pseudo-code, Sedgewick and Wayne work with real code, so that the programs can quickly be put to practical use. Programs are written in Java, but in a style such that most of the code can be reused to develop implementations in other modern programming languages. |
Data typesSedgewick and Wayne use a modern programming style based on data abstraction, so that algorithms and their data structures are encapsulated together. |
ApplicationsEach chapter has a detailed description of applications where the algorithms described play a critical role. These range from applications in physics and molecular biology, to engineering computers and systems, to familiar tasks such as data compression and searching on the web. |
A scientific approachThe emphasizes developing mathematical models for describing the performance of algorithms, using the models to develop hypotheses about performance, and then testing the hypotheses by running the algorithms in realistic contexts. |
Breadth of coverage
Segewick and Wayne’s primary goal is to introduce the most important algorithms in use today to as wide an audience as possible. These algorithms are generally ingenious creations that, remarkably, can each be expressed in just a dozen or two lines of code. As a group, they represent problem-solving power of amazing scope. They have enabled the construction of computational artifacts, the solution of scientific problems, and the development of commercial applications that would not have been feasible without them.
They cover basic abstract data types, sorting algorithms, searching algorithms, graph processing, and string processing. They keep the material in algorithmic context, describing data structures, algorithm design paradigms, reduction, and problem-solving models. They cover classic methods that have been taught since the 1960s and new methods that have been invented in recent years.
Great content. Printing could be better
Reviewed in the United States on May 29, 2020
I started reading "Algorithms" after Sedgewick and Wayne' s "Computer Science: An Interdisciplinary Approach," which I think is a great place to start for those who are new to (object-oriented) programming. This book, Algorithms, (and the Coursera course or the COS 226 at Princeton) builds your knowledge further by fleshing out the theory behind the data structures. I only made it through the first 3 chapters so far, but I think I became better at writing cleaner, concise, and correct code by reading this book and doing some coding assignments (of the Coursera course, which is based on this book and/or the course COS 226 at Princeton which uses this book). I like this book and the exercises because they provide a good mix of theory and practice. I feel like this book is great preparation for interviews, as well as for further study from books which use pseudo-code.The content itself is great, but I am deducting a point because of the print quality of the textbook. For some reason, a lot of the pages in my copy look grayer than they should. I'm not sure if it's a book formatting issue where the font color was set to gray accidentally or if it is a publisher issue, but for some pages the black text just doesn't appear as crisp and dark. I attached some pictures but my phone seems to color correct things and the difference in the photos doesn't seem big. In person, the variation in the black text throughout the book is definitely noticeable, though.
Reviewed in the United States on May 29, 2020
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Reviewed in the United States 🇺🇸 on November 20, 2014
Reviewed in the United States 🇺🇸 on May 29, 2020
The content itself is great, but I am deducting a point because of the print quality of the textbook. For some reason, a lot of the pages in my copy look grayer than they should. I'm not sure if it's a book formatting issue where the font color was set to gray accidentally or if it is a publisher issue, but for some pages the black text just doesn't appear as crisp and dark. I attached some pictures but my phone seems to color correct things and the difference in the photos doesn't seem big. In person, the variation in the black text throughout the book is definitely noticeable, though.
Great content. Printing could be better
Reviewed in the United States 🇺🇸 on May 29, 2020
I started reading "Algorithms" after Sedgewick and Wayne' s "Computer Science: An Interdisciplinary Approach," which I think is a great place to start for those who are new to (object-oriented) programming. This book, Algorithms, (and the Coursera course or the COS 226 at Princeton) builds your knowledge further by fleshing out the theory behind the data structures. I only made it through the first 3 chapters so far, but I think I became better at writing cleaner, concise, and correct code by reading this book and doing some coding assignments (of the Coursera course, which is based on this book and/or the course COS 226 at Princeton which uses this book). I like this book and the exercises because they provide a good mix of theory and practice. I feel like this book is great preparation for interviews, as well as for further study from books which use pseudo-code.Reviewed in the United States 🇺🇸 on May 29, 2020
The content itself is great, but I am deducting a point because of the print quality of the textbook. For some reason, a lot of the pages in my copy look grayer than they should. I'm not sure if it's a book formatting issue where the font color was set to gray accidentally or if it is a publisher issue, but for some pages the black text just doesn't appear as crisp and dark. I attached some pictures but my phone seems to color correct things and the difference in the photos doesn't seem big. In person, the variation in the black text throughout the book is definitely noticeable, though.
Images in this review
Reviewed in the United States 🇺🇸 on June 25, 2013
Top reviews from other countries
Anthony Lauder
A good first book for algorithms
Reviewed in the United Kingdom 🇬🇧 on September 25, 2015Amazon Customer
One of the best books
Reviewed in the United Kingdom 🇬🇧 on August 22, 2019Evgeny
Lack of clarity, ambiguous problems
Reviewed in Canada 🇨🇦 on February 16, 2022
