On 16:56 Mon 21 Mar     , Brian Dolbec wrote:
> There is an app called shogun-toolbox  http://www.shogun-toolbox.org/
> 
> that is designed specifically for machine learning.  It has many 
> interface capabilities including python (which they state has the most 
> complete documentation).  There is also many examples for it's use.
> 
> I personally don't know nearly enough about it to know what modeling 
> methods might be suitable or even if there is one suitable for this 
> type of model.  But I think should be investigated.  Implemented this 
> would have the potential to increase it's success rate over time, 
> reducing developer load even more.

This sounds like something that might be beyond a GSoC project to 
develop a standalone code base. It would probably work better next year 
as an enhancement, if this year's project to build an initial working 
application worked out well.

What I would do instead is a "smart" detection using things like 
flex/bison/pybison. You could first detect the buildsystem type 
(autotools/cmake/distutils/etc) based on file existence. Then you would 
parse the build files using the syntax described for your lexical 
analyzer/parser to build a basic understanding of what build-time 
options are available and offer them as USE flags. You could also do 
similar things to detect dependencies by understanding their syntax in 
the source code.

-- 
Thanks,
Donnie

Donnie Berkholz
Admin, Summer of Code
Gentoo Linux
Blog: http://dberkholz.com