Customer Reviews

Data Structures Outside-In with Java

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Venugobal makes a good choice in teaching data structures via the java interfaces. After all, as a java programmer, if you are learning some new java package, this is exactly how you probably learn it. A major point about the object oriented approach and encapsulation is to hide implementation details as lower level stuff.

So what happens in the book is that while learning about various data structures in the general sense, you can also quickly code and learn about using them. By availing yourself of those built into java. The standard java packages summarise a lot of effort by Sun in writing stable, highly debugged structures.

Of course, in a book like this, you do also need to understand implementations. A given data structure and algorithms that use it should not be a total black box. Hence, there are many details about sorting routines, queue implementations and tree traversals. There is a reasonable amount of rigour. Though the book is not at the level of Knuth's Art of Computer Programming, The, Volumes 1-3 Boxed Set (2nd Edition) (The Art of Computer Programming Series). Venugopal's exercises are a lot simpler than Knuth's.

However, if you are a java programmer, and you want to focus on what you are likely to most use, try looking into the hash table. In my java coding experience, the java Hashtable and HashSet are really common and useful entities. It turns out that they are also very easy to learn to use.

This book seems like it didn't make it to the editor. Semantic and not-semantic errors are abound. The author understands what he is trying to express, but didn't do it correctly. What the author presents as fact is hardly the same, so be wary about this book, and check examples given against other resources.

This is the just another professor trying to make money, rather than being an expressive book.

The only redeeming attribute is a simplified look at O notation as a price tag for a method call. It is easier to get your mind around than big notation at first, and because the author's background is in parallel computations, he is well qualified to assert this analogy. Be wary though, because in real world optimization it is important to have a firm grasp of what big "O" means, with respect to data size.