Agenda:
* Who am I?
* What is this course about?
* What will we be doing in this course?
* Describing functions with contracts
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Who am I:
Brian Noble
[email protected]
4753 CSE (upstairs)
Office hours: after class, 1:302:30 MW
or by appointment.
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Big ideas:
thinking before hacking is important
dealing with complexity is the #1 problem in programming.
this class is all about that.
Course Manifesto:
Mathematicsespecially as used by physicsis the formalism
we use to describe "what is"
> we model the physical world with equations
> solutions to those equations give us insight into
the physical reality around us
But, classical mathematics does not say anything about how these
processes unfold.
For that, we need something else.
Computer science is the formalism we use to describe "how to".
Algorithm: An abstract sequence of actions composed to solve a
problem.
example: walking
put left foot in front of right foot.
put right foot in front of left foot.
repeat. :)
Program: concrete set of *program statements*, expressed in some
*formal language*, which *implements* some algorithm.
Note: usually we use "program" to mean an executable binary (like
"winword" or "ls") but, in this definition, any
implementation of an algorithm can be considered a
program.
The task of programming:
1) Given a (possibly incomplete/imprecise) specification
2) Design an *effective* algorithm
3) Implement that algorithm *correctly* and *efficiently*
An algorithm is *effective* if:
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 it correctly satisfies the specification
 it is efficient in its (asymptotic) usage of *space* and *time*
Note: "asymptotic" performance does not prescirbe a particular running
time or size.
Rather, it tells us how running time/space requirements
grow every time we e.g. double the size of the problem to which the
algorithm is applied.
An implementation of an algorithm is *correct* if it behaves as the
alogorithm is intended for all inputs/in all situations.
Correctness
is never negotiable.
There are three notions of *efficient* implementations
 the implementation has (concrete) space/time requirements
"similar to" the abstract requirements of the corresponding
algorithm.
(This in the asymptotic sense).
 of all of the "asymptotically good" possible implementations,
this one is among the better ones in absolute, concrete terms.
 it does not take an undue amount of programmer effort to (a)
write the implementation in the first place (simplicity) or
(b) improve/adapt the implementation to more general/closely
related algorithms. (elegance)
So, efficient can mean fast, simple and/or elegant. This doesn't seem
that difficult.
What's the big deal?
Several big problems:
 Engineering: faster, better, cheaper: pick two
Unfortunately, our goals are often in conflict.
* The easiest programs to understand/modify are often not the
easiest to write.
* Programs that are simple to write/understand are often not
the absolute fastest possible solution to a problem.
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 Winter '08
 NOBLE
 ObjectOriented Programming, Abstraction, procedural abstraction

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