Greetings -
I'm finally finished review, here's what I heard:
============ from Tobias Verbeke:
[EMAIL PROTECTED] wrote:
> Greetings!
>
> After a quick look at current programming tools, especially with regards
> to unit-testing frameworks, I've started looking at both "butler" and
> "RUnit". I would be grateful to receieve real world development
> experience and opinions with either/both. Please send to me directly
> (yes, this IS my work email), I will summarize (named or anonymous, as
> contributers desire) to the list.
>
I'm founding member of an R Competence Center at an international
consulting company delivering R services
mainly to the financial and pharmaceutical industries. Unit testing is
central to our development methodology
and we've been systematically using RUnit with great satisfaction,
mainly because of its simplicity. The
presentation of test reports is basic, though. Experiences concerning
interaction with the RUnit developers
are very positive: gentle and responsive people.
We've never used butler. I think it is not actively developed (even if
the developer is very active).
It should be said that many of our developers (including myself) have
backgrounds in statistics (more than in cs
or software engineering) and are not always acquainted with the
functionality in other unit testing frameworks
and the way they integrate in IDEs as is common in these other languages.
I'll soon be personally working with a JUnit guru and will take the
opportunity to benchmark RUnit/ESS/emacs against
his toolkit (Eclipse with JUnit- and other plugins, working `in perfect
harmony' (his words)). Even if in my opinion the
philosophy of test-driven development is much more important than the
tools used, it is useful to question them from
time to time and your message reminded me of this... I'll keep you
posted if it interests you. Why not work out an
evaluation grid / check list for unit testing frameworks ?
Totally unrelated to the former, it might be interesting to ask oneself
how ESS could be extended to ease unit testing:
after refactoring a function some M-x ess-unit-test-function
automagically launches the unit-test for this particular
function (based on the test function naming scheme), opens a *test
report* buffer etc.
Kind regards,
Tobias
============ from Tony Plate:
Hi, I've been looking at testing frameworks for R too, so I'm interested
to hear of your experiences & perspective.
Here's my own experiences & perspective:
The requirements are:
(1) it should be very easy to construct and maintain tests
(2) it should be easy to run tests, both automatically and manually
(3) it should be simple to look at test results and know what went wrong
where
I've been using a homegrown testing framework for S-PLUS that is loosely
based on the R transcript style tests (run *.R and compare output with
*.Rout.save in 'tests' dir). There are two differences between this
test framework and the standard R one:
(1) the output to match and the input commands are generated from an
annotated transcript (annotations can switch some tests in or out
depending on the version used)
(2) annotations can include text substitutions (regular expression
style) to be made on the output before attempting to match (this helps
make it easier to construct tests that will match across different
versions that might have minor cosmetic differences in how output is
formatted).
We use this test framework for both unit-style tests and system testing
(where multiple libraries interact and also call the database).
One very nice aspect of this framework is that it is easy to construct
tests -- just cut and paste from a command window. Many tests can be
generated very quickly this way (my impression is that is is much much
faster to build tests by cutting and pasting transcripts from a command
window than it is to build tests that use functions like all.equal() to
compare data structures.) It is also easy to maintain tests in the face
of change (e.g., with a new version of S-PLUS or with bug fixes to
functions or with changed database contents) -- I use ediff in emacs to
compare test output with the stored annotated transcript and can usually
just use ediff commands to update the transcript.
This has worked well for us and now we are looking at porting some code
to R. I've not seen anything that offers these conveniences in R.
It wouldn't be too difficult to add these features to the built-in R
testing framework, but I've not had success in getting anyone in R core
to listen to even consider changes, so I've not pursued that route after
an initial offer of some simple patches to tests.mk and wintests.mk.
RUnit doesn't have transcript-style tests, but it wasn't very difficult
to add support for transcript-style tests to it. I'll probably go ahead
and use some version of that for our porting project. (And offer it to
the community if the RUnit maintainers want to incorporate it.) I also
like the idea that RUnit has some code analysis tools -- that might
support some future project that allowed one to catalogue the number of
times each code path through a function was exercised by the tests.
I just looked at 'butler' and it looks very much like RUnit to me -- and
I didn't see any overview that explained differences. Do you know of
any differences?
cheers,
Tony Plate
============== from Paul Gilbert:
Tony
While this is not exactly your question, I have been using my own system
based on make and the tools use by R CMD build/check to do something I
think of as unit testing. This pre-dates the unit-testing frameworks, in
fact, some of it predates R. I actually wrote something on this at one
point: Paul Gilbert. R package maintenance. R News, 4(2):21-24,
September 2004.
I have occasionally thought about trying to use RUnit, but never done
much because I am relatively happy with what I have. (Inertia is an
issue too.) I would be happy to hear if you do an assessment of the
various tools.
Best,
Paul Gilbert
============= From Seth Falcon:
Hi Tony,
[EMAIL PROTECTED] writes:
> After a quick look at current programming tools, especially with regards
> to unit-testing frameworks, I've started looking at both "butler" and
> "RUnit". I would be grateful to receieve real world development
> experience and opinions with either/both. Please send to me directly
> (yes, this IS my work email), I will summarize (named or anonymous, as
> contributers desire) to the list.
I've been using RUnit and have been quite happy with it. I had not
heard of butler until I read your mail (!).
RUnit behaves reasonably similarly to other *Unit frameworks and this
made it easy to get started with as I have used both JUnit and PyUnit
(unittest module).
Two things to be wary of:
1. At last check, you cannot create classes in unit test code and
this makes it difficult to test some types of functionality. I'm
really not sure to what extent this is RUnit's fault as opposed
to limitation of the S4 implemenation in R.
2. They have chosen a non-default RNG, but recent versions provide a
way to override this. This provided for some difficult bug
hunting when unit tests behaved differently than hand-run code
even with set.seed().
The maintainer has been receptive to feedback and patches. You can
look at the not-so-beautiful scripts and such we are using if you look
at inst/UnitTest in: Category, GOstats, Biobase, graph
Best Wishes,
+ seth
=================== Discussion:
After a bit more cursory use, it looks like RUnit is probably the right
approach at this time (sorry Hadley!). Both RUnit and butler have a
range of testing facilities and programming support tools. I support the
above statements about feasibility and problems -- except that I didn't
get a chance to checkout the S4 issues that Seth raised above. The one
piece that I found missing in my version was some form of GUI based
tester, i.e. push a button and test, but I think I've not thought through
some of the issues with environments and closures yet that might cause
problems.
Thanks to everyone for responses! It's clear that there is a good start
here, but lots of room for improvement exists.
Best regards / Mit freundlichen Grüssen,
Anthony (Tony) Rossini
Novartis Pharma AG
MODELING & SIMULATION
Group Head a.i., EU Statistical Modeling
CHBS, WSJ-027.1.012
Novartis Pharma AG
Lichtstrasse 35
CH-4056 Basel
Switzerland
Phone: +41 61 324 4186
Fax: +41 61 324 3039
Cell: +41 79 367 4557
Email : [EMAIL PROTECTED]
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