Path: utzoo!utgpu!jarvis.csri.toronto.edu!mailrus!wuarchive!udel!rochester!uhura.cc.rochester.edu!sunybcs!sbcs!stealth!brnstnd
From: brnstnd@stealth.acf.nyu.edu (Dan Bernstein)
Newsgroups: comp.software-eng
Subject: Re: CS education [engineering, mathematics, and computer science]
Message-ID: <4059@sbcs.sunysb.edu>
Date: 27 Nov 89 23:22:25 GMT
References: <2608@fai.UUCP> <34818@regenmeister.uucp> <9924@june.cs.washington.edu>
Sender: news@sbcs.sunysb.edu
Reply-To: brnstnd@stealth.acf.nyu.edu (Dan Bernstein)
Distribution: usa
Organization: IR
Lines: 17

In article <9924@june.cs.washington.edu> peterd@june.cs.washington.edu (Peter C. Damron) writes:
> Computability and complexity theory is unrelated to numerical analysis.

There are two sides to complexity theory. Theoretical complexity theory
(better called computability theory) studies issues like P = NP.
Practical complexity theory (what ``computational complexity theory''
used to mean) studies fast algorithms for practical problems.

Particular problems in practical complexity theory (e.g., computing pi
to many digits; or computing the sine of a floating-point number) have
quite a lot to do with numerical analysis.

(I'm in math, not computer science. Computability theory is definitely
CS; numerical analysis is definitely math; computational complexity
theory is somewhere in between.)

---Dan


Brought to you by Super Global Mega Corp .com