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The Definition of Standard ML (Computational models of cognition and perception)
 
 
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The Definition of Standard ML (Computational models of cognition and perception) [Paperback]

Robin Milner (Author), Mads Tofte (Author), Robert Harper (Author)
4.0 out of 5 stars  See all reviews (3 customer reviews)


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The Definition of Standard ML - Revised The Definition of Standard ML - Revised 4.0 out of 5 stars (3)
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Book Description

February 14, 1990 Computational models of cognition and perception
This book presents the official, formal definition of the programming language ML including the rules for grammar and static and dynamic semantics. ML is the most well-developed and prominent of a new group of functional programming languages. On the cutting edge of theoretical computer science, ML embodies the ideas of static typing and polymorphism and has also contributed a number of novel ideas to the design of programming languages.

Contents: Syntax of the Core. Syntax of Modules. Static Semantics for the Core. Static Semantics for Modules. Dynamic Semantics for Modules. Programs.

Appendixes: Derived Forms. Full Grammar. The Initial Static Basis. The Initial Dynamic Basis. The Development of ML.

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About the Author

Robin Milner was Professor Emeritus of Computer Science at the University of Cambridge, UK, and Professor at the Informatics Forum in the University of Edinburgh.

Mads Tofte is Vice Chancellor, IT University of Copenhagen.

Robert Harper is a Professor of Computer Science at Carnegie Mellon University.

Product Details

  • Paperback: 114 pages
  • Publisher: The MIT Press (February 14, 1990)
  • Language: English
  • ISBN-10: 0262631326
  • ISBN-13: 978-0262631327
  • Product Dimensions: 9.2 x 6.2 x 0.5 inches
  • Shipping Weight: 1.8 pounds
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (3 customer reviews)
  • Amazon Best Sellers Rank: #6,333,214 in Books (See Top 100 in Books)

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16 of 16 people found the following review helpful:
5.0 out of 5 stars BECOME the language!, June 5, 2000
By A Customer
To explain it in the words of the authors: "The keystone of the method [used to define Standard ML in this book], then, is a certain kind of assertion that takes the form B |- P => M and may be pronounced: 'Against the background B, the phrase P evaluates to the meaning M.' The formal purpose of this Definition is no more, and no less, than to decree exactly which assertions of this form are true."

Standard ML is a very powerful language because of the abilities it grants and the restrictions it enforces. While reading this book will not teach you SML, it will help reinforce its subtle elegance. If you have developed an infatuation with this language, you will not be able to resist the only book that truly contains it.

While not necessary to enjoy this volume, a prerequisite to have any understanding of its contents is some sort of background in type theory and mathematical logic that a course like this one taught by Harper... can only begin to provide.

And remember, ML loves you!

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1 of 1 people found the following review helpful:
5.0 out of 5 stars How language definitions should be done, June 17, 2007
This book is a lesson to programming languages everywhere. The language definition is succinct, accurate, and to the point. Anyone who has attempted to penetrate such documents as the ANSI C or C++ standard is met with hundreds of pages of ambiguous, confusing language, about which formal reasoning is next to impossible. By contrast, this book describes the language syntax and semantics in a precise, mathematical style, making actual implementation of the language straightforward, as well as providing a usable definition for reasoning about the correctness of implementations. This is an example of how language definitions should be done.
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1 of 5 people found the following review helpful:
2.0 out of 5 stars Cryptic, November 21, 2006
This book was apparently written by Math PHDs for use by Math PHDs. I found it to be pretty impenetrable. With this sort of language report, and the shortage of "how to" books for beginners, SML is probably doomed to obscurity, which is unfortunate.
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Inside This Book (learn more)
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First Sentence:
This document formally defines Standard ML. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
inference rules, tyvarseq valbind, tyvarseq tycon, exp atexp, infix status, identifier status, equality attribute, phrase classes, static semantics, signature expressions, dynamic semantics, value identifiers, value declaration, semantic objects
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