Boris Borcic wrote: > This reminds me of an early programming experience that left me with a > fascination. At a time where code had to fit in a couple dozens kilobytes, > I once had to make significant room in what was already very tight and > terse code. Code factoring *did* provide the room in the end, but the > fascinating part came before. > > There was strictly no redundancy apparent at first, and finding a usable > one involved contemplating code execution paths for hours until some > degree of similarity was apparent between two code path families. And > then, the fascinating part, was to progressively mutate both *away* from > minimality of code, in order to enhance the similarity until it could be > factored out. > > I was impressed; in various ways. First; that the effort could be > characterized quite mechanically and in a sense stupidly as finding a > shortest equivalent program, while the subjective feeling was that the > task exerted perceptive intelligence to the utmost. Second; by the notion > that a global constraint of code minimization could map more locally to a > constraint that drew code to expand. Third; that the process resulted in > bottom-up construction of what's usually constructed top-down, mimicking > the willful design of the latter case, eg. an API extension, as we might > call it nowadays.
This is much the same that happens in maximisation problems: the value gets trapped in a local maximum, and the only way to reach a greater global maximum is to go downhill for a while. I believe that hill-climbing algorithms allow some downhill movement for just that reason. Genetic algorithms allow "mutations" -- and of course real evolution of actual genes also have mutation. -- Steven -- http://mail.python.org/mailman/listinfo/python-list
