C.A.R. Hoare 1980 ACM Turing Award Lecture
started 6/12/2003; 9:33:21 AM - last post 6/15/2003; 10:14:45 AM
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Isaac Gouy - C.A.R. Hoare 1980 ACM Turing Award Lecture
6/12/2003; 9:33:21 AM (reads: 745, responses: 2)
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The Emperor's Old Clothes C.A.R. Hoare 1980 ACM Turing Award Lecture
Laugh and learn!
I have learned more from my failures than can ever be
revealed in the cold print of a scientific article and now
I would like you to learn from them, too. Besides, failures are much more fun to hear about afterwards; they are not so funny at the time...
Programmers are always surrounded by complexity;
we cannot avoid it. Our applications are complex because
we are ambitious to use our computers in ever more
sophisticated ways. Programming is complex because of the large number of conflicting objectives for each of our
programming projects. If our basic tool, the language in
which we design and code our programs, is also complicated, the language itself becomes part of the problem
rather than part of its solution.
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Neel Krishnaswami - Re: C.A.R. Hoare 1980 ACM Turing Award Lecture
6/14/2003; 4:56:56 AM (reads: 768, responses: 1)
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There are some really amazing observations in this article; take a look at this:
The principle of compactness of object code is even more valid today, when processors are trivially cheap in comparison with the amounts of main store they can address, and backing stores are comparatively even more expensive and slower by many orders of magnitude.
That's still true, even today, 23 years later. The only difference is that you'd need to replace "backing store" with "RAM", and "main store" with "instruction cache". This demonstrates the fact that computer performance is on an exponential growth curve very clearly, since there's a self-similarity law for such curves.
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Frank Atanassow - Re: C.A.R. Hoare 1980 ACM Turing Award Lecture
6/15/2003; 10:14:45 AM (reads: 771, responses: 0)
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The only difference is that you'd need to replace "backing store" with "RAM", and "main store" with "instruction cache".
Good point.
This demonstrates the fact that computer performance is on an exponential growth curve very clearly, since there's a self-similarity law for such curves.
Hardly. While there is undoubtedly a wealth of data to support Moore's Law (is that what you meant?), not only is two a poor sample size, but any recursively definable function evidently obeys at least one self-similarity law. :)
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