Hi Nicholas,
You raise a very good point. As an R user (who develops a couple of
packages for our own local use), I sometimes find myself cringing in
anticipation of a new R (or BioConductor) release. In my perception
(which is almost certainly exaggerated, but that's why I emphasize that
it is only an opinion), clever theoretical arguments in favor of
structural changes have a tendency to outweigh practical considerations
of backwards compatibility.
One of my own interests is in "reproducible research", and I've been
pushing hard here at M.D. Anderson to get people to use Sweave to
enhance the reproducibility of their own analyses. But, more often than
I would like, I find that reports written in Sweave do not survive the
transition from one version of R to the next, because either the core
implementation or one of the packages they depend on has changed in some
small but meaningful way.
For our own packages, we have been adding extensive regression testing
to ensure that the same numbers come out of various computations, in
order to see the effects of either the changes that we make or the
changes in the packages we depend on. But doing this in a nontrivial
way with real data leads to test suites that take a long time to run,
and so cannot be incorporated in the nightly builds used by CRAN.
We also encourage our analysts to include a "sessionInfo()" command in
an appendix to each report so we are certain to document what versions
of packages were used.
I suspect that the sort of validation you want will have to rely on an
extensive regression suite test to make certain that the things you need
remain stable from one release to another. That, and you'll have to be
slow about upgrading (which may mean foregoing support from the mailing
lists, where a common refrain in response to bug reports is that "you
aren't using the latest and greatest version", without an appreciation
of the fact that there can be good reasons for not changing something
that you know works....).
Best,
Kevin
Nicholas Lewin-Koh wrote:
Hi,
Kudos, nice exposure, but to make this more appropriate to R-devel I
would just
like to make a small comment about the point made by the SAS executive
about getting
on an airplane yada yada ...
1) It would seem to me that R has certification documents
2) anyone designing airplanes, analyzing clinical trials, etc. had
better be worried about a lot more than whether their software is
proprietary.
So from that point of view it would seem that R has made great strides
over
the last 5 years especially in establishing a role for open source
software solutions in regulated/ commercial
environments. The question now is how to meld the archiac notions of
validation and
and verification seen in industry with the very different model of open
source
development? Rather than the correctness of the software, in which I
think R is competitive,
it is how to deal with the rapid release cycles of R, and the
contributed packages.
We pull our hair out in pharma trying to figure out how we would ever
reconcile CRAN and validation requirements. I have no brilliant
soulution,
just food for thought
Nicholas
------------------------------
Message: 5
Date: Thu, 8 Jan 2009 13:02:55 +0000 (GMT)
From: Prof Brian Ripley <rip...@stats.ox.ac.uk>
Subject:Re: [Rd] NY Times article
To: Anand Patil <anand.prabhakar.pa...@gmail.com>
Cc: r-devel@r-project.org
Message-ID: <alpine.lfd.2.00.0901081258470.5...@auk.stats.ox.ac.uk>
Content-Type: TEXT/PLAIN; charset=US-ASCII; format=flowed
It has been all over R-help, in several threads.
https://stat.ethz.ch/pipermail/r-help/2009-January/184119.html
https://stat.ethz.ch/pipermail/r-help/2009-January/184170.html
https://stat.ethz.ch/pipermail/r-help/2009-January/184209.html
https://stat.ethz.ch/pipermail/r-help/2009-January/184232.html
https://stat.ethz.ch/pipermail/r-help/2009-January/184237.html
and more
On Thu, 8 Jan 2009, Anand Patil wrote:
Sorry if this is spam, but I couldn't see it having popped up on the list
yet.
http://www.nytimes.com/2009/01/07/technology/business-computing/07program.html?emc=eta1
Anand
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Brian D. Ripley, rip...@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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