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C00001 00001
C00002 00002 notes
C00005 00003
C00006 00004 EECS 129
C00012 00005 part zero: interactive computing (computing is the wrong word! --EXPRESSION?)
C00015 00006 Part one: Functions as passive objects
C00022 00007 Part two: Functions as active objects
C00024 00008 EECS 129: The Art of Computer Science
C00035 ENDMK
Cā;
notes
art
music
architecture
rhetoric
linguistics
history
anthro
phil
bio
physics
math
cs
eng
phisiology: homer smith
take susman example in "constraints"
see zen pp 332
?quality in obj?
?quality in prog?
relate godel, einstein, jmc and time??
--------------------------------------------
"non-technical" considerations
Does "computing" represent a "new culture" in the sense of spengler?
is there any "sense" to spengler?
--------------------------------------------
lab stuff
disks
paper
manuals
projects
first day stuff:
name, major, what you expect from this course.
idea for project, if you have one.
--------------------------------------------
lisp:
an object-oriented language in which
objects have "first-class" standing.
an object is an abstraction whose identity
can be described such that one can
recognize the existence of an obj
how?
1. recognizer
2. constant
construct a new one, given the necessary components
how?
constructor
select its components
how?
1. atomic and has no components
2. composite and have selectors
interesting object in lisp:
function!!!!!
--------------------------------------------
relate 432
--------------------------------------------
auto:horse = x: computer ---what's "x"?
what is mathematics?
people to ask, chowning, fred, avron, bil lewis,
Navy
68k
steamer
model ii multi-bank
cai
intelligent systems
prime
automated drafting
data bases
ti
lisp machine
portable
real-time
national
16K
open
rolm
8086
office automation
tlc
applications
education (cf. logo/smalltalk)
ai (visicalc)
people:
2 senior-full
2 mid-half
----------------------
mapper-based memory
ti-based lm
EECS 129
books: Zen and the art of motorcycle maintenance --Robert Pirsig
read it at least three times this term
Mindstorms -- Seymour Papert
what CAN be done with computing, if you try.
Godel, Escher, Bach -- Doug Hofstadter
an interesting view of mathematics, music, and art.
predule to Godel's incompleteness results (some much
better handled in LISP)
Jean Piaget -- Margaret Boden
particularly the last chapters (Piaget and X)
Anatomy of LISP -- John Allen
computer science from the LISP perspective
Functional Programming -- Peter Henderson
simplified version of LISP
The Gamesman(?) -- Michael Maccoby
interesting view of how modern coprorations view themselves,
particularly the role of the "craftsman"
Decline of the West(?) -- Oswald Spengler
philosophy of history, relating the "life" of a culture in terms
of its view of mathematics.
Men of Mathematics --E T. Bell
good perspective on the mathematical world
History of Western Philosophy -- B. Russell
Russell's "unbiased" view of the philosophical world
general systems theory stuff (?)
Kamongo: The Lungfish and the Padre -- Homer Smith
a phisiologist's "novel" about life and evolution
From Fish to Philosopher --Homer Smith
the kidney: from amoeba to Kant.
The Sufis --Idries Sha
a view of the world
Don Juan in Hell (act three of man and superman) --G B Shaw
GBS on life
Computer Power and Human Reason -- Joe Weizenbaum
sigh! some very good, some very BAD!
hysterical opportunism, in general.
class notes
interactive computing
wccf papers
lisp notes
papers: the ACM Turing lectures, in particular: Minsky, Scott-Rabin, Iverson
Newell-Simon, Floyd, Perlis, Backus, McCarthy.
software: mince: a display-based editor (Mince Is Not Complete Emacs)
logo: graphics-based sugar-coated functional language.
lisp: vanilla-flavored functional language.
visicalc: cute constraint-based business hack.
mu-math: symbolic mathematics package (micro-Macsyma)
zork: second generation Adventure.
db lang: reasonable relational/ai-based db language --TBA
c, (?): mumble
Each Friday we will summarize the week and integrate technical
aspects into the larger view of that makes these results relevant.
week 1: start the "where" (we're going)
M overview; read zen
where
what
how
wow
T read mindstorms ch 1-2
TH discuss MS 1-2
F read MS 3
lab logo
week 2: start the "what" (is computation)
M discuss MS 3
start the computational ideas
use geb, and formal theory ideas
T
TH ms 4
F
lab: mince
logo
visicalc (?)
mu-math (?)
random LISPs
week 3: start the "how" (it's done)
M how graphics ms 5-6
T
TH how lisp (computation) ms 7-*
F
lab: lisp
week 4: evaluation
M
T
TH
F
lab: more lisp/logo
week 5: object-oriented
M
T
TH
F
lab:
week 6: applications
M
T
TH
F
lab:
week 7: architecture
M a lisp machine
T
TH intel 432?
F
lab:
week 8: start the "wow"
* smalltalk: learning research group
* rubiks: tom davis
phil: sfs
pre-socratics:?
* graphics/music: scott kim, ***
* zork: bruce daniels
* theory: ****, jra
music: ***
geb: ***
nl: ?
expert systems
visicalc
vlsi: ?
part zero: interactive computing (computing is the wrong word! --EXPRESSION?)
low expectations, based on economics of last 20 years
graphics vs. keypunch
re-creation of 1965 on micros: very unfortunate
kids (of all ages)
LOGO, samlltalk, pie
lisp as explainer
lisp ā” object-oriented language
with all objects "1-st class"
(e.g. programs as objects)
harrangue
interactive composition vs. programming
composition
creative rhetoric
the rationale
the tools: instrument-like (H Smith)
the effect: ego-less
programming
what does programming represent?
ways of thinking (algorithmically)
read minsky's turing lecture
simulation of complex phenom.
can programmers be literate?
literacy=?
***weizenbaum's anti-hacker view
methodology vs. style
Part one: Functions as passive objects
1 Notation
The role of notation in science
expressivity
subordination of detail
economy
amenability to proof
The impact of computing on notation
executability
representability of algorithms
The difficulties with programming languages
Computation and interaction
The relationship between language and its medium
why computing languages cannot be separated
from the programming env
cf. conversation and understanding
The polarization between interaction and discipline
pascal vs. lisp vs. smalltalk
The polarization between rigor and hacking
basic vs. (lisp/scheme)
2 The language
3 Data domain: The whole numbers
Algorithmic notation
conditional expressions
definitions
recursion
numerical examples
computation as deduction
axioms for number theroy
rules of inference
substitution and simplification
number theory
conditional
the concept of proof
equivalence
termination
truth, computation, and deduction
what is truth?
truth versus deduction
incompleteness results
the appropriate language
elementary number theory
something better
Data Domain: symbolic expressions
the representability of programs
abstract objects
constructors, selectors, and recognizers
The mapping of expressions to data structures
Non-numeric computation: examples
evaluation of polynomials
simplification of algebraic expressions
propositional logic: evaluation
?theorem proving
binary trees (l-n-r) rep, sort, add, del
missionaries and cannibal
game stuff
4 Evaluation
5 Deduction vs computation, again
systems for substitution and simplification
computation as controlled deduction
call-by-name vs. call-by-value
Semantics of programming languages
Representability of programs
a detailed discussion
An evaluation algorithm
The operational view
Implementation strategies
call-by-value
weak vs. strong conditional
simulation of substitution
extending the evaluator
macros and read-macros: abbreviational convenience
iteration: language extension and special forms
6 A modern LISP: more data structuring
7 The idea of "first-class data"
implementation-driven languages violate notational principles
arbitrary precision numbers
Strings
Arrays
property-lists (flex records)
modules/labels: organizational
8 Property-lists and message passing
classes as properties
algorithms as message passing
hieracharies and flavors
hierarchies as implementation simplification
9 Object-oriented programming
10 Smalltalk and Actors
frames and flavors
11 Lexical vs dynamic scoping: the beginnings of active functions
Evaluation revisited
functionals
the difficulty with functional arguments
variables: local, free, global
added complexity of functional values
12 Control: function vs algorithm
an analysis of the evaluator
the run-time structure
stacks
stacks+access and control links
tree access, control stack
tree access, tree control
control as data: reflective systems
13 Applicative v.s. imperative
control as a programming tool
side-effects
assignment, rplaca, rplacd
14 Implementation considerations
implementation of the evaluation process
read
parsers and scanners
searching and hashing
print
runtime language support
i-j pairs
shallow versus deep
run-time data support
numbers
arbitrary precision numbers
trees
programmer maintained
reference counting
garbage collection
mark sweep
copy-compacting
cheney
baker
henry&carl
15 Machines and compiling
16 The LISP machine
Traditional machines as microcode
Compilation
program representation
list structure
scheme hacks
p-code/byte code/MACRO
machine specific
Hardware
LISP machine
Scheme chips
14 The Racks paper: a bridge from passive to active
Part two: Functions as active objects
1 Functions as first-class objects
Relationship between
purity:lexical and
utility: dynamic
interactive creation of functional objects
programming in "levels": modules
2 Applications of functional objects
car,cdr, cons as:
1. arrays and functional
2. pure functional (t, f)
3. 1 as msg passing
3 stacks as functionals (gls/gjs)
4 multiprocessing (wand/aip)
5 Evaluation of Functionals
evaluators for full funarg
evaluators for smalltalk (ingalls)
6 Applications of lisp-related computing
cad
nl
business data bases --must do much better here
7 The future of computing
interactive programming
language designs
theory
ai applications
EECS 129: The Art of Computer Science
This course is a challenge. I plan to challenge your conception of what
computing is about, to challenge the traditional view of the purpose programming
languages, to challenge the usual conception of how one does programming, to
challenge the traditional curriculum of computing, and in general to challenge
your minds.
The course is neither mathematics nor engineering; it draws from both
disciplines, as does all of computer science. The intent of the course is to
investigate the phenomena called computing at a level of abstraction that will
allows us to explicate fundamental principles that underlie computing theory and
practice.
The texts for this course are "Zen and the Art of Motorcycle Maintenance", and
"Mindstorms: Computers, Children, and Powerful Ideas". Class notes will form
the main structure of the technical and "meta-computational" perspective that
supports the inquiry. "Zen" has valuable insights in the relationships between
art and science, besides the appropriate "tone" for this course. "Mindstorms"
is good fun: an exemplary book showing how one can present complex ideas in an
intuitive, yet faithful, setting.
A lab session is associated with this course. Since part of our exploration
involves computing, it is a requirement that one understands the art of
computing --often called "programming". Learning to program is like learning to
drive --both can profit from classroom work that explains basic concepts.
However both require "hands-on" experience before one really gets "the feel" of
the instrument. As with driving school, we should supply the students with the
best available vehicles and guide them in the process of applying the theory.
There are two important practical lessons in the programming experience: first
to develop an appreciation for abstraction and abstract programming, and second
to develop an understanding of how interactive programming differs from the
traditional "batch" (or modified "batch")-processing view. Abstract
object-oriented programming carried out in an interactive programming
environment is the future of applied computing.
The course will be a self-contained "mind-stretcher": no prerequsites other
than a healthy intellectual curiousity and the self-discipline to think.
However, the work will be demanding, so it is suggested that you have at least a
3.0 G.P.A. in your major.
WHAT I EXPECT: A lot! Though the course will be self-contained, I will not
"spoon-feed" you. You will be expected to delve into areas other than your
major course of study: mathematics, philosophy, education, art, and history are
all fair game. Hopefully, there will be a sufficiently diverse background in
this class that knowledge can be pooled. If not, you (and I) will have to dig.
If you have questions, understand where you lost track; simply saying "I don't
get it" is not satisfactory.
COURSE WORK: Show up every day! Do not get behind! By the end of the fourth
week, have a project outline ready to turn in and discuss with me in a 15 minute
interview.
Possible areas for topics: history, philosophy, education, mathematical theory
of computation, language design, machine architecture, language implementation,
applications (graphics, art, artificial intelligence).
COURSE GRADING: Difficult! Some programming, some "fact extraction", some
essays. Style and quality will count in all these efforts.
Programming = 10%
Midterm = 30%
Project = 30%
Final = 30%
THE COURSE INTENT: To destroy the university
***give details
GENERAL DISCLAIMER If you are one of those students who feels that the only
grade is an "A" and will drop if your GPA is threatened, then this course is not
for you. For you "late dropper"s: be considerate and drop early. Don't waste
your time or hold a slot in this class that someone else might use. Who knows,
I might not sign drop slips!?!
COURSE READING: There is a list of required and suggested books for this class.
***NO WRITING IN THE LIBRARY BOOKS, DAMN IT*** Some illiterate slob destroyed
the library copy of "Don Juan in Hell".
COURSE LAB: This is area requires the most cooperation from everyone.
Resources are very limited, though there's reason to believe that things will
improve. All recources --machines, documentation, and disks-- are at a premium;
most things are borrowed, so be particularly careful.