Description Details Author(s) References See Also Examples
A complete unit test system and functions to implement its GUI part.
The SciViews 'svUnit' package defines a framework for testing R code, not
unlike jUnit for Java. It is inspired on the checkxxx()
functions from the
'RUnit' package and the same test unit files should be compatible with both
'svUnit' and 'RUnit'. However, the internal implementation is completely
different and svUnit can also be used interactively, while 'RUnit' is only
designed to run test units written in files on disks.
The test unit framework provided in 'svUnit' is based on tests, also called
assertions, implemented in checkxxx()
functions. For instance, the
checkTrue(expr)
function check if its 'expr' argument returns TRUE
.
Results of these assertions are collected in a centralized logger located in
the .Log
object in .GlobalEnv
. This is a 'svSuiteData' object with data
about the context of the tests (see for instance, lastTest()
, lastSuite()
or metadata(.Log)
).
Assertions can give three results: (1) TRUE
if success, (2) FALSE
in
case of failure (in our example, 'expr' in checkTrue(expr)
did not return
TRUE
), and (3) NA
if the code in 'expr' cannot be parsed or executed
correctly. All these errors or failures are catch and recorded in the logger,
as individual 'svTestData' objects.
Both the logger ('svSuiteData' object) and test records inside it
('svTestData' objects) have convenient methods to visualize information they
contain: print()
, summary()
and stats()
methods. Access to the
individual test records in the logger is done with list-like instructions:
.Log$mytest
returns the 'svTestData' object named 'mytest', itself the
result of running test in the 'mytest' test function (i.e.,
runTest(mytest)
, see hereunder). Assertions run at the command line,
outside of specific contexts provided by test functions, test units and
test suites (see hereunder) are recorded under the 'eval' 'svTestData' object
in the logger (i.e., .Log$eval
).
Since a 'svSuiteData' object (the logger) is also an environment, you can get
the list of all test records it contains using ls(.Log)
, and you can
eliminate a given test record using rm(mytest, envir = .Log)
.
Test cases are collections of assertions with the satellite code needed to
build example or situations to be tested. They are collected together in
argument-less functions with class being 'svTest'. See ?svTest
for
further explanations and a couple of example test cases/test functions.
In its simplest instance, a test function is defined as a separate R object
loaded in memory (unlike RUnit where all test must be defined in files). You
run it simply by using runTest(mytest)
. A slightly more structured way
to work is to attach the test function to the object it testes. You use
test(myobj) <- testmyobj
to do so, and retrieve it with test(myobj)
. Now,
the test function always follows the tested object. Testing the object is
still simple by using runTest(myobj)
, which is totally equivalent to
runTest(test(myobj))
. One can determine if an object has a test function
associated, or is a test function itself by using is.test(myobj)
.
Several test functions can be collected together in so-called test units. A
test unit only exists on disk. It is a file named 'runit*.R' containing
sourceable R code with test functions having names starting with 'test'
(unlike 'RUnit', the default convention of file names starting with 'runit'
and test function names starting with 'test' is not customizable in
'svUnit'). One can also define special .setUp()
and .tearDown()
functions
in the test unit. The first function will be run before each test function,
and the latter one will be run after it. Test units are created manually, or
from a collection of objects with associated test functions loaded in an
environment (usually .GlobalEnv
) thanks to the makeUnit()
method. These
units should be mutually compatible with those used in the 'RUnit' package
(at least this is verified with version 0.4-17 of 'RUnit').
Test units defined for packages should be located in the package /runitTests
subdirectory (/inst/runitTests for source of the package) or one of its
subdirectories. That way, they are located automatically by the function
svSuiteList()
that also automatically detects all objects with associated
test functions loaded in .GlobalEnv
. Test suites are 'svSuite'
objects with a list of test units or test objects to collect in the suite.
Thus, svSuiteList()
automatically builds such a suite with all tests it
finds in R, with many possibilities to filter packages' test units, objects'
test functions, or to add non standard directories with test units, for
instance. See ?svSuite
for more details on creating and using these
suites.
A GUI (Graphical User Interface) is provided to automatically build and run tests suites and to get a graphical (tree) interactive report of the results in the Komodo Edit or IDE code editor, together with the SciViews-K extension. If you want to use this (optional) GUI, you have to install required software components on your machine.
Finally, the 'svUnit' framework is compatible with R CMD check
(see the
manual "Writing R extensions"). You simply define man pages (.Rd files) with
an example section running selected test units from your package. The
function errorLog()
is designed to generate and error if one or more tests
failed or raised an error during R CMD check
, and it should be used at the
end of the example that runs your unit test(s). That way, R CMD check
is
interrupted and a detailed report of the tests that failed or raised an error
is printed. See an example in ?unitTests.svUnit
.
Written by Ph. Grosjean, inspired from the general design of the 'RUnit' package by Thomas Konig, Klaus Junemann & Matthias Burger.
There is a huge literature and unit testing. An easy starting point is: https://en.wikipedia.org/wiki/Unit_test.
Useful links:
Report bugs at https://github.com/SciViews/svUnit/issues
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | # Clear the logger
clearLog()
# Design and attach a simple test function to an object
foo <- function(x, y = 2)
return(x * y)
testfoo <- function() {
#DEACTIVATED() # Use this to deactive the test (notice placed in the log)
checkEqualsNumeric(5, foo(2), "Check return of foo()")
checkException(foo("b"), "Wrong first argument")
checkException(foo(2, "a"), "Wrong second argument")
}
# Attach this to the foo function
test(foo) <- testfoo
# Run this test
runTest(foo)
# Inspect the result
ls(.Log)
.Log$`test(foo)`
# This test fails. You see that the test function requires that foo(2) = 5
# and the actual implementation returns 4. This is a trivial, useless example,
# but you are supposed to correct the function. For instance:
foo <- function(x, y = 2)
return(x * y + 1)
test(foo) <- testfoo
(runTest(foo)) # Now, that's fine!
|
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