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Where Expectations Meet Reality: Realistic Unit Testing in R

realtest is a framework for unit testing for realistic minimalists; it aids in formalising:

  • assertions,
  • current behaviour that we'd like to see changed in the future,
  • alternative yet perfectly acceptable practices (e.g., when outputs are platform-dependent and should remain so),
  • requested features to be implemented in due time (e.g., as part of the monitoring of third-party software projects for changes).

The introduced vocabulary is (and will be kept!) minimalistic:

  • P is prototype – you can use it to manually create a descriptor like "I expect this function to return c(1, 2, 3), with a warning" or "that should result in an error";

  • R stands for record – creates a descriptor by evaluating an expression and capturing its direct and indirect effects:

    • values generated (together with object attributes),
    • errors,
    • warnings and messages,
    • text output on stdout and stderr;
  • E means expect – compares an expression under scrutiny (via R) with a series of descriptors (created via P or R and using a pairwise comparer provided) and stores the matching one (if any).


Some examples:

library("realtest")  # call install.packages("realtest") first

# identical
E(sqrt(4), 2.0)  # equivalent to E(sqrt(4), P(2.0))

# almost-equal (round-off errors)
E(sin(pi), 0.0, value_comparer=all.equal)

# two equally okay possible outcomes:
E(sample(c("head", "tail"), 1), "head", "tail")

# not-a-number, with a warning
E(sqrt(-1), P(NaN, warning=TRUE))

# desired vs. current vs. undesired (because it can always be worse!) behaviour
E(
    paste0(1:2, 1:3),                  # expression to test - concatenation
    best=P(                            # what we yearn for (ideally)
        c("11", "22", "13"),
        warning=TRUE
    ),
    current=c("11", "22", "13"),       # this is the behaviour we have now
    bad=P(error=TRUE)                  # avoid regression
    # and of course, everything else (un-expected) makes up a failed test
)

Refer to the on-line documentation at https://realtest.gagolewski.com/ for more details.

To learn more about R, check out Marek's open-access (free!) textbook Deep R Programming.


Package Maintainer and Author: Marek Gagolewski

Homepage: https://realtest.gagolewski.com/

CRAN Entry: https://CRAN.R-project.org/package=realtest

License: realtest is distributed under the terms of the GNU General Public License, either Version 2 or Version 3, see LICENSE

Changelog: see NEWS