hi,

that's interesting, i'd be curious to see where you go
with it, keep me informed. 

yeah logic failures, well, there probably is no scale.
if there is a failure, bad, if there are none, good,
correct? 

in that case it might be good to just run on random
'genomes'. and halt on failure, or run all night and
record all failures. a single failure would probably
give you plenty to go on, w/o being further evolved.

regards,
_c


--- Vidar Hokstad <vidar / edgeio.com> wrote:

> 
> Christophe Mckeon wrote:
> > http://drp.rubyforge.org
> >
> > i'll be doing a presentation tonight in
> secondlife, read the recent post
> > titled Rubyists of Second Life Meeting,
> 09/07/2006.
> 
> When I first saw this, I was thinking that it would
> be fun to play with
> whenever I get time to look at evolutionary
> programming again, but it
> just hit me that there's another place where this
> project would be very
> useful:
> 
> Testing. I was just writing some code to generate
> sequences of test
> operations, and I remembered this project - using it
> to generate test
> scripts from a grammar seems to be  a good fit. The
> question would be
> what type of search algorithm to use, and if using a
> GA etc. what would
> make sense for a fitness function.
> 
> In the latter case, I guess it depends on the
> purpose of the testing:
> In the case of performance, using a fitness function
> that assigns
> higher fitness the lower the system performance
> would encourage test
> scripts that converge on patologically bad
> performing cases. In the
> case of logic failures, it may be tricky to assign a
> gradual scale of
> failures, and I'm not really sure if a GA would be a
> good search
> alogrithm for that case. 
> 
> Vidar
> 
> 
> 



	
	
		
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