From: Albert Wagner Date: 2002-09-08T03:29:44+09:00 Subject: Re: Larry Wall's comments on Ruby On Saturday 07 September 2002 12:42 pm, Christian Szegedy wrote: > Albert Wagner wrote: > > < snip> > > > >>I wonder whether you know what complexity theory is about... > > > > I thought I knew, but maybe not. Tell us. A link would do. > > > >>Regards, Christian > > The complexity theory deals with (mainly asymptotic) runtime > a space efficiency of algorithms and networks. > It is *not* about design considerations in complex programs. > > > http://www.complexitytheory.com/ > > It's just a course overview, but you can get some impressions. > > The part you snipped was: > > "Which, geven the time of his rise to ascendency would be expected. We > are all a product of "our times". While complexity theory has been > around since the 70's (some would say off and on since the time of the > Egyptians) but was not widely known outside of very tight academic > circles before the mid-90's. Thus, Larry can be forgiven for thinking > the concept of "objects" too difficult for the beginner." > > At least I don't see how Complexity Theory fits into this sentence > unless it was meant sarcastically. > > Regards, Christian Thank you for your reply and the link. I am incompetent to argue the point. My computer education has been completely informal. However, from my perspective, I don't see in the overview at that link anything that precludes the principles from applying to a complex program. I suppose that there is either another "complexity theory" or the one that you pointed me to has been bastardized in the pop science community. My understanding was that OOP technologies grew out of some sort of studies in complexity, and were an attempt to deal with that complexity. Somewhat related: I saw a graph some years ago that impacted on me. The y axis was randomicity and x was complexity. It was to illustrate that (a) if randomicity was sufficiently high then statistical methods were useful and (b) if randomicity was very low and complexity was low then standard mechanical methods were useful. What I found startling was the large area in the middle and to the right that were not random enough for statistics to be reliable and too complex for mechanical methods. Yet, it was just in this area, where no reliable tools currently existed that most of the interesting and important problems of our time existed.