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Resources
Here are some links to various resources on the Web that you might find useful. These include links to background material, news sites, and sites where you can learn about specific products.
Please contribute links to sites you may know about so that everyone can benefit from everyone else's knowledge and experience.
Standard ML
Running Standard ML
Generally the class will assume you are using a recent version of the Standard ML of New Jersey
compiler, a free compiler developed at Bell Labs (the current version is 110.55). You can run ML on turing
using the command sml, but if you'd rather use your own computer,
you can download it for most operating
systems, including Windows and Linux.
The CS 131 guide to using SML/NJ contains some very useful information on the mechanics of running the compiler, using it with emacs, and (perhaps most importantly) interpreting error messages.
Because SML has an official definition,
there are several other good, freely-available compilers available for the
language that you may use instead, including Moscow
ML (for many operating systems; it can also be run on turing via the command
mosml), Poly/ML (for many
operating systems) and MLton (for x86 machines).
Each implementation has its own advantages.
Learning Standard ML
If you've done some SML programming in the past, the shortest way to get up to speed may be to read through the SML Overview for CS 131. This is meant to summarize the minimum knowledge about SML needed to do the programming for this class. As such, it is very condensed; if you find it too compressed then you might want to look elsewhere:
- Robert Harper at Carnegie Mellon University has written a tutorial Programming in Standard ML (This is a rather long pdf file, so please don't send it to the college printers.) Chapter 1 jumps right into a relatively complex ML program; if this seems overwhelming you might go on to Chapter 2, which starts back at the beginning with a more introductory approach.
- Andrew Cumming has written A Gentle Introduction to ML
- There are several textbooks you can purchase on learning SML, including Jeffrey Ullman's Elements of ML Programming (ML97 Edition), Hansen and Rischel's Introduction to Programming Using SML, and Laurence Paulson's ML for the Working Programmer. Copies of all three books are also held on reserve at the Sprague circulation desk.
Documentation for the Standard ML Basis (i.e., the standard library) is available on-line. Particularly useful are the modules Int, Real, String, and List, but there are many others as well.
