On 2018-09-26 10:32, MacQueen, Don via R-devel wrote:
With regard to Martin's comment about the strength of (base) R:
I have R code I wrote 15+ years ago that has been used regularly ever since
with only a few minor changes needed due to changes in R. Within that code, I
find particularly impressive for its stability a simple custom GUI that uses
the tcltk package that has needed no updates whatsoever in all that time.
Such stability and reliability have been extremely valuable to me.
How much of R's stability is due to the unit tests encouraged by
the examples in the help pages, the vast majority of which are run
repeatedly with each new change?
More generally, what are the lessons the computer science
discipline can take from R's experience in this regard?
I discussed this eight years ago in an article on "Package
development process" that I posted to Wikipedia eight years ago that
has attracted 9 views per day since. I also added a table discussing
this to the Wikipedia article on "Software repository". That article has
attracted over 300 views per day for at least the past 3 years. Both
these articles could doubtless be improved by someone more knowledgeable
than I.
Many thanks and kudos to Ross Ihaka, Bob Gentleman, Martin
Maechler and the rest of the R Core team, who have managed this project
so successfully for more than two decades now.
Spencer Graves
-Don
--
Don MacQueen
Lawrence Livermore National Laboratory
7000 East Ave., L-627
Livermore, CA 94550
925-423-1062
Lab cell 925-724-7509
On 9/26/18, 12:41 AM, "R-devel on behalf of Martin Maechler"
<r-devel-boun...@r-project.org on behalf of maech...@stat.math.ethz.ch> wrote:
[-- most of original message omitted, so as to comment on the following --]
-----
*) {Possibly such an R we would create today would be much closer to
julia, where every function is generic / a multi-dispach method
"a la S4" .... and still be blazingly fast, thanks to JIT
compilation, method caching and more smart things.}
But as you know one of the strength of (base) R is its stability
and reliability. You can only use something as a "the language
of applied statistics and data science" and rely that published
code still works 10 years later if the language is not
changed/redesigned from scratch every few years ((as some ... are)).
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