R Core Team: Development Principles and War Stories · To: [email protected],...

Background The Core Team Development principles War stories

R Core Team: Development Principles andWar Stories

Peter Dalgaard

Center for StatisticsCopenhagen Business School

R Users Conference in Korea, May 30th 2014

1 / 27


Outline

Background

The Core Team

Development principles

War stories

2 / 27


Outline

Background

The Core Team


War stories

3 / 27


R’s history in brief

I S (c.1985), written by John Chambers et al. (ACM softwaresystems award 1998)

I Started approx.1994, Ross Ihaka & Robert Gentleman inAuckland

I Available via Internet 1996I Version 1.0.0 2000-02-29I Version 2.0.0 2004-10-04

4 / 27


Formation of the Core Team

1996 R mailing lists, testing, debugging, discussing1997 Invitation to join Core Team1999 First physical meeting in Vienna

5 / 27


Date: Sat, 16 Aug 1997 09:15:45 +1200 (NZST)From: Ross Ihaka <[email protected]>To: [email protected], [email protected],

[email protected]: Invitation ...Cc: [email protected], [email protected]

We have had a bit of a discussion on enlarging the R "core team" Atpresent this seems to consist of Robert, Martin and myself although thefollowing people also have commit privileges in the CVS tree:

Luke Tierney no introduction neededHeiner Schwarte developer of dyn.load etcPaul Murrell my PhD student

[...]As major contributors (and apparently sane people) we would like toinvite you to be part of the R "core team".[...]We can’t promise you anything much in return, except a free copy of R:-) and perhaps a publication on "distributed development of statisticalsoftware". Since you are clearly hopeless software junkies, perhaps youdon’t need any more incentive.[...]

6 / 27


Outline

Background

The Core Team


War stories

7 / 27


People on the Core Team

Ross Ihaka, Robert Gentleman Founding fathersKurt Hornik, Fritz Leisch CRAN maintenance, QC issuesUwe Ligges Windows builderSimon Urbanek Mac builds and support, BugzillaBrian Ripley Translation coordinator. Testing + a lot of stuff all

over the placeMartin Mächler Mailing lists, Matrix, lme4 packageLuke Tierney Computer language guru, compiler, garbage

collector, parallel processingPeter Dalgaard Release managementDuncan Murdoch Parser improvements, debuggingPaul Murrell Graphics

8 / 27


People on the Core Team, cont.

John Chambers S4 methodsDuncan Temple Lang Inter-language interfacesThomas Lumley Survey package, general biostats powerhouseDeepayan Sarkar Lattice graphicsMartyn Plummer Fedora/Red Hat connectionCurrently inactive Seth Falcon, Stefano Iacus, Doug Bates

9 / 27


Outline

Background

The Core Team


War stories

10 / 27


Steering

11 / 27


Themes

I Issues we need to tackleI Tools to make the task manageableI Release mechanisms

12 / 27


Basic principles

I Keep the base code maintainableI New functionality via packages, with separate maintainersI Careful and conservative development – avoid breaking

CRAN packages unnecessarilyI No master plan — core developers can do what they feel is

desirable (and face the consequences)

13 / 27


Computing Platforms

I R works on Windows, MacOS X and multiple Unix/Linuxvariants

I . . . and their variants over timeI Graphical User Interfaces (GUIs)I Operating system interfacesI Binary packaging formatsI Build configuration (flags, libraries, etc.)

14 / 27


Automating Things

I Version control (“Subversion” repository in Zurich)I The make program describes how to build targets from

subtargets using makefilesI The GNU Autotools create the configure script that sorts

out all the little system dependencies.I Common help file format (.Rd), tools to generate HTML,

latex, an plain text help filesI Package format specification and build tools

15 / 27


Testing and Checking

I Formal check — documentation consistent with functiondefinitions, all fields present in package descriptions, allexamples runnable, etc

I Run all examples and check for errorsI Specific testing, regression tests, targeted consistency

checksI Automated checks of all packages

16 / 27


Development Principles

I Statistical software development is slightly specialcompared to other software

I High emphasis on correctnessI Large amounts of legacy code (FORTRAN!)I Dependency on many tools

I Conservative, carefully tested releases

17 / 27


Release Process

I Need feedback from users, especially those on obscureplatforms

I Need stabilityI Phased releases (alpha/beta/RC)

18 / 27


Outline

Background

The Core Team


War stories

19 / 27


1. Development process sensitivity

The following story is a little technical, but it shows just howeasily apparently minor modifications can destabilize things(notice the dates!)

20 / 27


Exotic languages

Back in 2008 when R 2.7.1 was current, we received tworeports about R crashing under Windows XP. Both frommachines in Korea. The second one came in on August 7. Atthat point Brian Ripley set out to investigate and traced theissue to a faulty translation file, which he removed from thesources on August 11.

21 / 27


Rarely checked build steps

Meanwhile, on August 10 we had scheduled R 2.7.2 forAugust 25. When the release process started on the 15th, itturned out that the source package wouldn’t build. The makedist command listed the now absent translation file as adependency.So I commented out the offending line in the Makefile —somewhat carelessly, as it turned out.

22 / 27


Rare operating system anomalies

Not all versions of the make program allow you to usecomments. In particular, R would now not install on FreeBSD, aplatform that noone in R Core was using at the time.Fortunately, someone reported the problem on August 17, justbefore the code freeze on August 18.

23 / 27


2. Random Normals

In several cases, R has been instrumental in finding obscurebugs in algorithms

I Around version 1.6, R’s random number mechanism usedI the Marsaglia-Multicarry method as the base uniform

generatorI the Kinderman-Ramage method for normal variate

generationI Someone came up with the following example which

shows a set of strange ripples

RNGversion("1.6.0")s <- replicate(1e6,max(rnorm(100)))plot(density(s))

24 / 27


1 2 3 4 5

0.0

0.2

0.4

0.6

0.8

1.0

density(x = s)

N = 1000000 Bandwidth = 0.02365

Den

sity

25 / 27


Random Normals, cont’d

I Replacing the uniform generator removed the problemI Replacing the normal variate method also removed the

problemI The Kinderman-Ramage method is quite complicated, but

part of it is thatI one uniform number is used to decide whether the random

value is out in the tailI a second independent uniform number is used to decide

where in the tailI This particular usage pattern revealed an unfortunate

aspect of the Marsaglia-Multicarry method (therefore nolonger the default).

26 / 27


Summary

I R Core has a conservative and careful approach to themaintenance of R

I This can be a tricky job at timesI However, it contributes to

I The credibility of R as a viable platform for statisticalanalysis

I The long-term validity and reliability of statistical algorithms

27 / 27

R Core Team: Development Principles and War Stories · To: [email protected],...

Documents

Transcript of R Core Team: Development Principles and War Stories · To: [email protected],...