This book originated in lectures on Standard ml and functional programming. It can still be regarded as a text on functional programming — one with a pragmatic orientation, in contrast to the rather idealistic books that are the norm — but it is primarily a guide to the effective use of ml. It even discusses ml's imperative features.

Some of the material requires an understanding of discrete mathematics: elementary logic and set theory. Readers will find it easier if they already have some programming experience, but this is not essential.

The book is a programming manual, not a reference manual; it covers the major aspects of ml without getting bogged down with every detail. It devotes some time to theoretical principles, but is mainly concerned with efficient algorithms and practical programming.

The organization reflects my experience with teaching. Higher-order functions appear late, in Chapter 5. They are usually introduced at the very beginning with some contrived example that only confuses students. Higher-order functions are conceptually difficult and require thorough preparation. This book begins with basic types, lists and trees. When higher-order functions are reached, a host of motivating examples is at hand.

The exercises vary greatly in difficulty. They are not intended for assessing students, but for providing practice, broadening the material and provoking discussion.

Overview of the book. Most chapters are devoted to aspects of ml. Chapter 1 introduces the ideas behind functional programming and surveys the history of ml.