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Purely Functional Data Structures

4.4 out of 5 stars 19 customer reviews
ISBN-13: 978-0521663502
ISBN-10: 0521663504
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Editorial Reviews

Review

"This book is important because it presents data structures from the point of view of functional languages...a handy reference for professional functional programmers...Most of the programs can easily be adapted to other functional languages. Even C and Java programmers should find implementing these data structures a relatively straightforward process...Programs are physically well structured and readable, and are displayed in boxes. Okasaki has produced a valuable book about functional programming, exploring a wide range of data structures...a significant contribution to the computer science literature." Computing Reviews

Book Description

Most books on data structures assume an imperative language like C or C++. However, data structures for these languages do not always translate well to functional languages such as Standard ML, Haskell, or Scheme. This book describes data structures and data structure design techniques from the point of view of functional languages. It includes code for a wide assortment both of classical data structures and of data structures developed exclusively for functional languages.This handy reference for professional programmers working with functional languages can also be used as a tutorial or for self-study.
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Product Details

  • Paperback: 232 pages
  • Publisher: Cambridge University Press (June 13, 1999)
  • Language: English
  • ISBN-10: 0521663504
  • ISBN-13: 978-0521663502
  • Product Dimensions: 6 x 0.5 x 9 inches
  • Shipping Weight: 14.6 ounces (View shipping rates and policies)
  • Average Customer Review: 4.4 out of 5 stars  See all reviews (19 customer reviews)
  • Amazon Best Sellers Rank: #223,640 in Books (See Top 100 in Books)

Customer Reviews

Top Customer Reviews

Format: Paperback
Okasaki's slim volume is one of the best expositions on implementing data structures & algorithms in a functional language. After taking an introductory course on functional programming, this would be the book which tells you where to go next.

This book doesn't just present a rehash/rewrite of imperative data structures, only written in a functional language. Instead, Okasaki makes sure to emphasize benefits which only functional programming can bring to the table. For example, many functional data structures can compactly represent not just their current state, but all of their past states as well--a feature called "Persistence". Also, functional newbie programmers might be wondering why lazy vs. strict programming is a big deal, and Okasaki shows clearly where data structures can benefit from either being lazy or being strict.

For the advanced reader, Okasaki also presents several powerful techniques for analyzing the runtime of algorithms, including the so-called "Banker's Method" and the "Physicist's Method" for analyzing amortized algorithms.

I hope that Okasaki comes out with a 2nd edition of this book; there is one missing piece in particular which I really wish he would have included: Although he presents an EXTREMELY lucid description of how to implement Red-Black trees in a functional language, he only presented algorithms for insertion and querying. Of course, deletion from a red-black tree is the hardest part, left here, I suppose, as an exercise to the student. If you want to supply this missing piece yourself, check out a paper by Stefan Kars, "Red-black trees with types", J. Functional Programming 11(4):425-432, July, 2001.
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Format: Paperback
[This review copied from my moribund blog at [...] ]

The typical data structures most programmers know and use require imperative programming: they fundamentally depend on replacing the values of fields with assignment statements, especially pointer fields. A particular data structure represents the state of something at that particular moment in time, and that moment only. If you want to know what the state was in the past you needed to have made a copy of the entire data structure back then, and kept it around until you needed it. (Alternatively, you could keep a log of changes made to the data structure that you could play in reverse until you get the previous state - and then play it back forwards to get back to where you are now. Both these techniques are typically used to implement undo/redo, for example.)

Or you could use a persistent data structure. A persistent data structure allows you to access previous versions at any time without having to do any copying. All you needed to do at the time was to save a pointer to the data structure. If you have a persistent data structure, your undo/redo implementation is simply a stack of pointers that you push a pointer onto after you make any change to the data structure.

This can be quite useful--but it is typically very hard to implement a persistent data structure in an imperative language, especially if you have to worry about memory management [1]. If you're using a functional programming language--especially a language with lazy semantics like Haskell--then all your data structures are automatically persistent, and your only problem is efficiency (and of course, in your functional languages, the language system takes care of memory management).
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Despite the editorial description of the book, the book is really about Standard ML. It happens to have an appendix where source code has been translated -- out of order, and without reference to the text -- into Haskell. This makes it very difficult to read through the book without speaking Standard ML.

The exercises, also, are only SML. Several appear to use idiosyncratic SML features -- I say "appear" because no answers to the exercises, even the basic ones, are provided for me to check my understanding.

Essentially, the content is good, but expect to learn Standard ML to really get the most out of this book.
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Format: Paperback
The description of the book says it includes source code in both ML and Haskell. Unfortunately, the body of the text uses ML exclusively, and the Haskell code is banished to an appendix.

I say "unfortunately", because many of the data structures used depend on lazy evaluation, which comes quite naturally to Haskell, and seems to require some sort of non-standard extension in ML.

While the content is good, I wish it would have used Haskell as the primary exposition language.
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I'm not going to lie; I didn't make it through the second 2/3rds of this book. But that first third did more for my understanding of functional programming than the rest of my FP library did combined. This book seems to me to be the functional programming answer to Design Patterns. It's worth having on your shelf if you have any interest in functional programming, ML, or Haskell.
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