Introduction
Run-time testing with assertive
Development-time testing with testthat
Writing easily maintainable and testable code
Integrating testing into your packages
Writing your own assertions and expectations
Answers to exercises
Richard Cotton
"This timely book of about 180 pages by Richard Cotton provides
detailed, hands-on instructions on how to improve the correctness,
stability, and user-friendliness of R scripts and packages through
testing.
Written in an entertaining and informal style … [a]ll concepts and
functions used in the book are introduced and demonstrated with
real code, which should be a very valuable resource to readers and
helps keep one engaged throughout. …
All in all, this book addresses two very important topics—how to
implement reliable, flexible input checks, and human-readable error
messages and how to formalize the expected behavior of an R
package—in a well-structured, hands-on, and eminently readable
manner. It is a timely and important addition to the literature on
programming with R, with lots of motivating examples. I look
forward to teaching proper testing procedures in my advanced R
programming classes based on it."
—Fabian Scheipl, Ludwig-Maximilians-University Munich, in
Biometrical Journal, August 2017"…provides all the guidance you’ll
need to write robust, correct code in the R language…useful advice
for organizing and writing code that's more maintainable in the
long run…Testing is a topic that doesn't get as much attention as
it deserves in data science disciplines. One reason may be that
it's a fairly dry topic, but Cotton does a good job in making the
material engaging with practical examples and regular exercises
(with answers in the appendix). Frequent (and often amusing)
footnotes help make this an entertaining read (given the material)
and hopefully will motivate you to make testing a standard (and
early) part of your R programming process."
—David Smith, Microsoft Research, on Revolutions, March 2017"When
it comes to getting things right in data science, most of the focus
goes to the data and the statistical methodology used. But when a
misplaced parenthesis can throw off your results entirely, ensuring
correctness in your programming is just as important. This book
provides all the guidance you’ll need to write robust, correct code
in the lingua franca of data science, R. These practical techniques
will help you implement development-time and run-time checks in
your code, and the worked examples will get you up to speed
quickly. And with the confidence that your code is actually doing
what it’s supposed to, you can look forward to more maintainable
and — most importantly — reliable results."
—David Smith, Microsoft Research"This book will teach you to test
both your analysis code and your functions. Richie is a great
teacher: the book is approachable and fun, and you'll be able to
immediately apply what you learn. Along the way, you'll also get
some great tips about writing high-quality code in R."
—Hadley Wickham (RStudio)"Writing clear, reliable tests is an
essential part of programming in R. In this book, Richie Cotton
covers the various approaches you can take - approaches I use in
writing my R packages and production-ready code - in a useful,
comprehensive and eminently readable manner."
—Oliver Keyes (ironholds.org, @quominus)"In short, I loved it.
There is a dearth of good material (or any material, really) on
this topic so I'm excited to say that 'Testing R Code' met my high
expectations. I know the subject rather well but, not only did I
see topics that were explained in new and easier ways than I have
previously seen, but I even learned quite a bit of new information
myself. It is obvious that the author knows this topic inside and
out."
—Tony Fischetti, Rensselaer Polytechnic Institute
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