**Implementing Functional Languages: a tutorial**

by Simon Peyton Jones, David Lester

**Publisher**: Prentice Hall 1992**ISBN/ASIN**: B001UHUR8W**Number of pages**: 296

**Description**:

This book gives a practical approach to understanding implementations of non-strict functional languages using lazy graph reduction. The book is intended to be a source of practical labwork material, to help make functional-language implementations 'come alive', by helping the reader to develop, modify and experiment with some non-trivial compilers.

Download or read it online for free here:

**Download link**

(multiple formats)

## Similar books

**The Z Notation: A Reference Manual**

by

**J. M. Spivey**-

**Prentice Hall**

The standard Z notation for specifying and designing software has evolved over the best part of a decade. This an informal but rigorous reference manual is written with the everyday needs of readers and writers of Z specifications in mind.

(

**6765**views)

**Categories, Types, and Structures**

by

**Andrea Asperti, Giuseppe Longo**-

**MIT Press**

Here is an introduction to category theory for the working computer scientist. It is a self-contained introduction to general category theory and the mathematical structures that constitute the theoretical background.

(

**12703**views)

**Formal Syntax and Semantics of Programming Languages**

by

**Kenneth Slonneger, Barry L. Kurtz**-

**Addison Wesley Longman**

The book presents the typically difficult subject of formal methods in an informal, easy-to-follow manner. Readers with a basic grounding in discreet mathematics will be able to understand the practical applications of these difficult concepts.

(

**10463**views)

**The Design and Implementation of Probabilistic Programming Languages**

by

**Noah D. Goodman, Andreas Stuhlmüller**-

**dippl.org**

This book explains how to implement PPLs by lightweight embedding into a host language. We illustrate this by designing WebPPL, a small PPL embedded in Javascript. We show how to implement several algorithms for universal probabilistic inference.

(

**1324**views)