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The Definition of Standard ­ML
The MIT Press

Rating
Format
Paperback, 132 pages
Published
United States, 21 May 1997

Standard ML is a general-purpose programming language designed for large projects. This book provides a formal definition of Standard ML for the benefit of all concerned with the language, including users and implementers. Because computer programs are increasingly required to withstand rigorous analysis, it is all the more important that the language in which they are written be defined with full rigor.One purpose of a language definition is to establish a theory of meanings upon which the understanding of particular programs may rest. To properly define a programming language, it is necessary to use some form of notation other than a programming language. Given a concern for rigor, mathematical notation is an obvious choice. The authors have defined their semantic objects in mathematical notation that is completely independent of Standard ML.In defining a language one must also define the rules of evaluation precisely--that is, define what meaning results from evaluating any phrase of the language. The definition thus constitutes a formal specification for an implementation. The authors have developed enough of their theory to give sense to their rules of evaluation."The Definition of Standard ML" is the essential point of reference for Standard ML. Since its publication in 1990, the implementation technology of the language has advanced enormously and the number of users has grown. The revised edition includes a number of new features, omits little-used features, and corrects mistakes of definition.


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Product Description

Standard ML is a general-purpose programming language designed for large projects. This book provides a formal definition of Standard ML for the benefit of all concerned with the language, including users and implementers. Because computer programs are increasingly required to withstand rigorous analysis, it is all the more important that the language in which they are written be defined with full rigor.One purpose of a language definition is to establish a theory of meanings upon which the understanding of particular programs may rest. To properly define a programming language, it is necessary to use some form of notation other than a programming language. Given a concern for rigor, mathematical notation is an obvious choice. The authors have defined their semantic objects in mathematical notation that is completely independent of Standard ML.In defining a language one must also define the rules of evaluation precisely--that is, define what meaning results from evaluating any phrase of the language. The definition thus constitutes a formal specification for an implementation. The authors have developed enough of their theory to give sense to their rules of evaluation."The Definition of Standard ML" is the essential point of reference for Standard ML. Since its publication in 1990, the implementation technology of the language has advanced enormously and the number of users has grown. The revised edition includes a number of new features, omits little-used features, and corrects mistakes of definition.

Product Details
EAN
9780262631815
ISBN
0262631814
Publisher
Other Information
Ill.
Dimensions
22.8 x 17.8 x 1.1 centimeters (0.25 kg)

Table of Contents

Part 1 Syntax of the core: reserved words; special constants; comments; identifiers; lexical analysis; infixed operators; derived forms; grammar; syntactic restrictions. Part 2 Syntax of modules: reserved words; identifiers; infixed operators; grammar for modules; syntactic restrictions. Part 3 Static semantics for the core: simple objects; compound objects; projection, injection and modification; types and type functions; type schemes; scope of explicit type variables; non-expansive expressions; closure; type structures and type environments; inference rules; further restrictions. Part 4 Static semantics for modules: semantic objects; type realization; signature instantiation; functor signature instantiation; enrichment; signature matching; inference rules. Part 5 Dynamic semantics for the core: reduced syntax; simple objects; compound objects; basic values; basic exceptions; function closures; inference rules. Part 6 Dynamic semantics for modules: reduced syntax; compound objects; inference rules. Part 7 Programmes. Part 8 Appendices.

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. Robert Harper is a Professor of Computer Science at Carnegie Mellon University. David MacQueen is Professor of Computer Science at the University of Chicago. Mads Tofte is Vice Chancellor, IT University of Copenhagen.

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