ML for the Working Programmer

Paulson, Lawrence C.

ISBN 10: 0521390222 / ISBN 13: 9780521390224

Edité par Cambridge University Press, 1991

A propos de cet article

Good. Ex-Library with usual stamps and stickers. Used with moderate to heavy wear to covers and corners, sunning to spine. Age-toning to pages. NO markings and binding is sturdy. N° de réf. du vendeur mon0000681866

Détails bibliographiques

Titre : ML for the Working Programmer

Éditeur : Cambridge University Press

Date d'édition : 1991

Reliure : hardcover

Etat : Good

A propos de ce titre

Synopsis :

This practical book teaches the methods of functional programming, in particular, how to program in Standard ML. 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.

Présentation de l'éditeur:

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 are extensively used throughout. In addition, the first chapter has been totally rewritten to make the book more accessible to those without experience of programming languages. The main features of new Standard Library for the revised version of ML are described and many new examples are given, while references have also been updated. 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 the Internet) from the author. He shows how to use lists, trees, higher-order functions and infinite data structures. Many illustrative and practical examples are included.. Efficient functional implementations of arrays, queues, priority queues, etc. are described. Larger examples include a general top-down parser, a lambda-calculus reducer and a theorem prover. The combination of careful explanation and practical advice will ensure that this textbook continues to be the preferred text for many courses on ML.