- Paperback: 500 pages
- Publisher: Cambridge University Press; 2 edition (Jun 28 1996)
- Language: English
- ISBN-10: 052156543X
- ISBN-13: 978-0521565431
- Product Dimensions: 2.5 x 1.8 x 0.3 cm
- Shipping Weight: 862 g
- Average Customer Review: 3.7 out of 5 stars See all reviews (3 customer reviews)
- Amazon Bestsellers Rank: #432,510 in Books (See Top 100 in Books)
- See Complete Table of Contents
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Product Details |
Product Description
Review
"The book is an excellent introduction to ML, but even better, it provides a good overview of functional programming." Jeffrey Putnam, Computing Review
Book Description
The new edition of this successful and established textbook retains its two original intentions of explaining how to program in the ML language, and teaching the fundamentals of functional programming. The major change is the early and prominent coverage of modules, which the author extensively uses throughout. In addition, Paulson has totally rewritten the first chapter to make the book more accessible to students who have no experience of programming languages. The author describes the main features of new Standard Library for the revised version of ML, and gives many new examples, e.g. polynomial arithmetic and new ways of treating priority queues. Finally he has completely updated the references. Dr. Paulson has extensive practical experience of ML, and has stressed its use as a tool for software engineering; the book contains many useful pieces of code, which are freely available (via Internet) from the author. He shows how to use lists, trees, higher-order functions and infinite data structures. He includes many illustrative and practical examples, covering sorting, matrix operations, and polynomial arithmetic. He describes efficient functional implementations of arrays, queues, and priority queues. Larger examples include a general top-down parser, a lambda-calculus reducer and a theorem prover. A chapter is devoted to formal reasoning about functional programs. The combination of careful explanation and practical advice will ensure that this textbook continues to be the preferred text for many courses on ML for students at all levels.
Inside This Book
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First Sentence
The first ML compiler was built in 1974. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
The first ML compiler was built in 1974. Read the first page
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Concordance
Browse Sample PagesConcordance
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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Customer Reviews
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Most helpful customer reviews
3.0 out of 5 stars
Completely mistitled,
By Idiosyncrat (California) - See all my reviews
This review is from: ML for the Working Programmer (Paperback)
This book is not bad; the explanation of all that it does explain is very good. It's just somewhat impractical, especially given the name; the title is a terrible misnomer for a book whose major example projects involve a lambda calculus evaluator and a proof assistant for first-order logic (not exactly the sort of thing "working" programmers usually have to do!). It does have some pretty solid demonstrations of how to implement various useful data structures and algorithms in SML (e.g. trees), but no "real-world" projects.The problem with this book is typical of the problem facing a lot of introductory material for many of the more academic languages-- they explain the theory behind the language very well and how the features work, but they don't really teach you how to organize programs in the language, stuff like what code to put in what file, when to use modules and functors, etc. If you cut your teeth in imperative OOP like I did, reading this book you might get to understand the features of this language, but without still being clear about how one would go about writing an actual program in it. Still, this is a book worth owning.
3.0 out of 5 stars
a good book, but it wasn't compelling for me,
By A Customer
This review is from: ML for the Working Programmer (Paperback)
I have no doubt this is a well-written book (I read it in its entirety). Unfortunately, the examples weren't compelling to me at all. While the lambda calculus interpreter was interesting, the time spent on the theorem prover was not very interesting (I wonder if it was added as an homage to ML's legacy??).Overall, I suppose this book is a little dated.
5.0 out of 5 stars
Good introductory book with some advanced chapters,
This review is from: ML for the Working Programmer (Paperback)
If you want to know something about ML, but learn it through good examples and interesting problems. This is the book! Also has some neat chapters on automated theorem proving, logic and interpreters.
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