Category: Scheme

Schematics Scheme Cookbook

Author (multiple)
Format online HTML
Price free

The Scheme Cookbook’s primary aim is show how common programming problems can be solved in Scheme via short programming “recipes”. Parts of the Cookbook are specific to PLT Scheme but we aim to provide portable solutions when possible.

Given the current lack of practical documentation for Scheme we also aim to cover areas of practical programming that fall outside the strict Cookbook remit. This includes topics such as Scheme idioms, Programming pearls, and Scheme code libraries.

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Structure and Interpretation of Computer Programs

  • Author: Harold Abelson, Gerald Jay Sussman, Julie Sussman
  • Format: online HTML
  • Price: free

An excellent computer science text used in introductory courses at MIT. So called because of the wizard on the jacket. One of the bibles of the LISP/Scheme world. Also, less commonly, known as the Purple Book.
from The New Hacker’s Dictionary, 2nd edition
(MIT Press, 1993)

On the site you will find the full text of the book, sample programming assignments, source code, and free implementations of the MIT Scheme programming environment.

Chapters include:

  • Building Abstractions with Procedures
  • Building Abstractions with Data
  • Modularity, Objects, and State
  • Metalinguistic Abstraction
  • Computing with Register Machines
  • References
  • List of Exercises

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How to Design Programs: An Introduction to Programming and Computing

  • Author: Matthias Felleisen, Robert Bruce Findler, Matthew Flatt, Shiram Krishnamurthi
  • Editon: September 2003 Version
  • Format: online HTML
  • Price: free

This book is on program design, geared more towards beginners, that presents many ‘design recipes’. The language used is Scheme, using DrScheme, a programming environment with special assistance for beginning students.

The DrScheme programming environment is freely available at the book’s official Web site.

Chapters include:

  • Processing Simple Forms of Data
  • Processing Arbitrarily Large Data
  • Abstracting Designs
  • Generative Recursion
  • Accumulating Knowledge
  • Changing the State of Variables
  • Changing Compound Values

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