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ML for the Working Programmer [Hardcover]

Lawrence C. Paulson (Author)
4.1 out of 5 stars  See all reviews (7 customer reviews)


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There is a newer edition of this item:
ML for the Working Programmer ML for the Working Programmer 4.1 out of 5 stars (7)
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Book Description

July 26, 1991
This book teaches the methods of functional programming--in particular, how to program in Standard ML, a functional language recently developed at Edinburgh University. The author shows how to use such concepts as lists, trees, higher-order functions and infinite data structures and includes a chapter on formal reasoning about functional programming. This is meant to be a practical book; the author avoids dogma, emphasizes efficiency, and provides many useful and interesting programs. These include fast sorting functions and efficient function implementations of arrays, queues, and priority queues. Examples also include a ^D*l-calculus reducer and theorem prover. Most features of ML (including modules and imperative programming) are covered in depth and the book can be used without an ML reference manual. The reader is assumed to have some experience in programming in conventional languages such as C or Pascal. For such individuals, be they students, graduates or researchers, this will be a convincing introduction to functional programming.

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Editorial Reviews

Review

"If you are an experienced programmer who wants to learn Standard ML, then this is the text for you. The book succeeds on two levels: as an introduction both to the strengths of functional programming in general, and to the intricacies of Standard ML in particular. It is filled with well-crafted programs that reveal the tricks of the functional programmer's trade. There is a readable explanation of the sophisticated modules system, and danger signs warn you of the few remaining infelicities in the language.....There is a fascinating collection of search algorithms, which illustrate with good effect how ML can mimic 'lazy' evaluation. These examples culminate in a wonderful final chapter that presents a theorem prover, of just the kind ML was created to support....Paulson writes with vigour and with humor. The book is spiced with jokes and polemics." Philip Wadler, Times Higher Education Supplement

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 prominent coverage of modules. --This text refers to the Paperback edition.

Product Details

  • Hardcover: 439 pages
  • Publisher: Cambridge University Press (July 26, 1991)
  • Language: English
  • ISBN-10: 0521390222
  • ISBN-13: 978-0521390224
  • Product Dimensions: 10 x 7 x 1.1 inches
  • Shipping Weight: 2 pounds
  • Average Customer Review: 4.1 out of 5 stars  See all reviews (7 customer reviews)
  • Amazon Best Sellers Rank: #1,872,396 in Books (See Top 100 in Books)

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Customer Reviews

7 Reviews
5 star:
 (3)
4 star:
 (2)
3 star:
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Average Customer Review
4.1 out of 5 stars (7 customer reviews)
 
 
 
 
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17 of 17 people found the following review helpful:
5.0 out of 5 stars Very Worthwhile, March 6, 2005
By 
If you are looking for a book that will help extend your professional qualifications this is not it. However if work through this book you will emerge with much stronger programming skills in any programming language and gain some important insights in to writing intelligent programs.

The book teaches Standard ML. Standard ML is a clean, modern, strongly typed, functional programming language. Some SML compilers generate code that ranks among the best for higher level languages. Standard ML comes out of a community that has been interested in developing logical theorem provers and tools for formal analysis of programs. Don't let this scare you away -- any reasonably bright programmer should be able to follow Paulson's explanations.

The book provides an accessible introduction to programming with recursive functions, higher order functions (functions that process functions) and working with a language with polymorphic types (a little like C++'s templates but the compiler figures out the types). This is as much a book on algorithms and data structures from a functional point of view as it is a book on Standard ML.

I especially like the book's development of more advanced examples in the last two chapters. These have to do with writing programs that implement some key ideas in logic and computability theory. These were easy to follow even for a non-expert. I have a strong interest in how programs can be made to reason and learn and so these were really interesting.
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33 of 37 people found the following review helpful:
3.0 out of 5 stars Completely mistitled, June 1, 2004
By 
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.

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3 of 3 people found the following review helpful:
4.0 out of 5 stars The past into the future?, March 22, 2008
My interest in learning ML started with reading the writings of people like Paul Graham who extoll the virtues of functional programming. ML seemed like the most accessible language for someone coming from an imperative oop background (due to the absence of '(' ... ')' which permeate Lisp and Scheme). There is however a dearth of introductory material on the web and what is out there seems to offer a piece meal, fragmentary overview. So I picked up this book and was not disappointed.

Paulson does an excellent job of introducing ML concepts in a clear logical manner. This book is about a lot more than ML though. Paulson teaches functional programming in this book with ML as the vehicle. This is a great book for self study. So why not five stars? The typesetting is horrendous. This is not a pretty book.

I think pretty much everyone will admit that ML never gained a lot of traction (Ocaml a bit more than SML I believe). The main problem I see with using ML for a large project is the lack of library support. So why learn ML? It turns out that ML has had an influence on new languages that have come out in recent years; F# and Scala are two. So time spent with ML should pay off when exploring these newer languages and whose close association with the .Net and Java platforms (respectively) cures the library availability dilemma.
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Inside This Book (learn more)
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First Sentence:
The first ML compiler was built in 1974. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
real list list, equality polymorphism, functor syntax, opaque signature constraint, type exn, val zip, forbidden variables, new standard library, functor body, abstype declaration, basic sequents, infix status, fun prod, polymorphic type checking, val prod, inst env, fun update, val declaration, int seq, filter pred, fun null, fun sub, char list, ind hyp, int list list
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Eight Queens, James Tyrrell, King Henry, Jack Cade, New Jersey, David Turner
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