Elements of ML Programming, ML97 Edition

Elements of ML Programming, ML97 Edition, 2/e

Jeffrey D. Ullman, Stanford University

Published December, 1997 by Prentice Hall Engineering/Science/Mathematics

See other books about:
ML--Programming-Computer Science

Programming Languages/Comparative Languages-Computer Science

Functional Programming-Computer Science

Summary

Written by renowned computer science educator and researcher Jeffrey Ullman, this text assumes no previous knowledge of ML or functional programming. This second edition has been heavily revised and updated using ML 97. This is the first book that offers BOTH a highly accessible, step-by-step introductory tutorial on ML programming and a complete explanation of advanced features. The author uses a wide variety of program examples to show how ML can be used in a variety of applications. More sophisticated programs and advanced concepts make this book usable in a number of courses for self-study or class discussion.

Summarizes the entire ML 97 language including the latest SML/NJ features.
The author, who is a data structure pioneer, shows how standard structures and problems (e.g., hashing, binary trees, solving linear equations, numerical integration, and sorting) are implemented with ML.
Makes ML programming interesting for the uninitiated.
Demonstrates the power and ease of functional programming with a variety of interesting small and large program examples .
Gives an and accurate overview of important ML syntax and semantic subtleties.
Uses pedagogy that highlights key concepts
d pitfalls with easy to use lists and bullets.
Has a flexible organization that can be adapted to introductory or intermediate/advanced courses.
Covers the module system and functions.
Explores the array structure.

Table of Contents

1. A Perspective on ML and SML/NJ.
2. Getting Started in ML.
3. Defining Functions.
4. Input and Output.
5. More about Functions.
6. Defining Your Own Types.
7. More about ML Data Structures.
8. Encapsulation and ML Module System.
9. Summary of the ML Standard Basis.
Index.