Relay-Version: version B 2.10 5/3/83; site utzoo.UUCP
Posting-Version: version B 2.10.2 9/18/84; site cca.UUCP
Path: utzoo!watmath!clyde!burl!ulysses!bellcore!decvax!cca!g-rh
From: g-rh@cca.UUCP (Richard Harter)
Newsgroups: net.cse
Subject: Re:  CS degrees, are they useful?
Message-ID: <6420@cca.UUCP>
Date: Wed, 26-Feb-86 22:08:23 EST
Article-I.D.: cca.6420
Posted: Wed Feb 26 22:08:23 1986
Date-Received: Sat, 1-Mar-86 00:48:56 EST
References: <6350@cca.UUCP> <>
Reply-To: g-rh@cca.UUCP (Richard Harter)
Organization: Computer Corp. of America, Cambridge
Lines: 38
Summary: 

In article <> ladkin@kestrel.ARPA (Peter Ladkin) writes:
>In article <6350@cca.UUCP>, g-rh@cca.UUCP (Richard Harter) writes:
>> [curriculum for a CS degree]
>> EE/MATH: Statistical theory of communication and linear systems.
>> Math:  Calculus, advanced calculus for engineers, linear algebra,
>> mathematical statistics (the hard core stuff, not "statistics for
>> grade school teachers"), and numerical analysis.
>
>This would be almost entirely useless to anyone but a numerical
>analyst.
>What about propositional and predicate calculus, complexity
>theory (concrete and asymptotic), graph theory, combinatorics,
>some universal algebra (plus a bit of groups, rings and fields
>for concreteness), Boolean algebra, relational algebra, model
>theory, theory of computation, theory of formal languages,
>recursion theory (Turing machines, recursive functions),
>lambda calculus and denotational semantics?
>Or did you forget these?

Mostly forgot -- I trained as a mathematician/physicist and worked
for a while on a PhD in mathematical logic so I tend to forget
that people actually have to learn math.  However I will contend
that for most applications mathematical logic is of no particular
value.  Almost every thing that you list is of importance or is
critical for pure computer science and is of no particular value
in end user applications except algebra.

On the other hand, if you are going to work in scientific and
engineering applications you should have a working knowledge of
numerical analysis.  At a guess I would say that 60% of all
programming is commercial applications, 30% is scientific/
engineering applications, and 10% is systems.  If you are not
in commercial applications you will, more likely than not, be
working with engineers.  That's where the jobs are and that is
what most people should be training for.  Mind you, this is just
my opinion, but it backed by experience and observation.

	Richard Harter, SMDS Inc.