I'm teaching myself Lisp for fun & (hopefully) profit, and would like a
little advice from you experienced Lispers/Schemers. A multi-pronged
approach seems most natural to me:
Prong-0: Using MIT C-Scheme, work through the famous SICP book and
possibly parts of _Essentials of Prog. Lang._ by Friedman, Wand, &
Haynes.
Prong-1: Learn industrial-strength, practical Lisp coding
techniques from Norvig's recent book, plus tricks of the trade from
the interesting new book _On Lisp_ by Paul Graham.
Prong-2: Read other people's Lisp code, write my own.
My questions:
What's the best *inexpensive* Common Lisp
interpreter/compiler/debugger... for DOS/Windows? According to the
FAQ, the basic choices are: NanoLISP, Star Sapphire Common Lisp,
CLISP, and a beta-test version of KCL. (Later, I may want to learn
CLOS). I know this question is vague; let's just say I'm looking for
a good compromise between 'toy' implementations and the full-blown
development packages like Allegro CL.
Which of the many memos written at the MIT AI lab in the '70s by Guy
Steele et al. would be the most useful for self-study? (For example,
"The Art of the Interpreter...", "Debunking the Expensive Procedure
Call Myth", ...) These seem to appear in every bibliography on Lisp,
but are not easily available, hence my question.
Thanks in advance for your comments.
You may email your responses to me if that's more appropriate.
--
Mark A. Thomas
········@access.digex.net
In article <··········@access.digex.net> ········@access.digex.net (M. Thomas) writes:
> Which of the many memos written at the MIT AI lab in the '70s by Guy
>Steele et al. would be the most useful for self-study? (For example,
>"The Art of the Interpreter...", "Debunking the Expensive Procedure
>Call Myth", ...) These seem to appear in every bibliography on Lisp,
>but are not easily available, hence my question.
These memos are good for theoretical computer science curricula, but are
not really that interesting if you're more interested in practical aspects
of programming. They discuss esoteric programming language design and
implementation issues.
If you want to get these publications, though, here's the address:
Publications, Room NE43-818
M.I.T. Artificial Intelligence Laboratory
545 Technology Square
Cambridge, MA 02139 USA
Phone number: (617) 253-6773
Net address: ············@ai.mit.edu
There's an online index available via World Wide Web in URL
http://www.ai.mit.edu/aipub-index/pubs-index.html.
--
Barry Margolin
System Manager, Thinking Machines Corp.
······@think.com {uunet,harvard}!think!barmar