fuzzr
fuzzr implements some simple “fuzz tests” for your R functions, passing in a wide array of inputs and returning a report on how your function reacts.
Installation
install.package("fuzzr")
# Or, for the development version:
devtools::install_github("mdlincoln/fuzzr")
Usage
Tests are set by passing functions that return named lists of input
values. These values will be passed as function arguments. Several
default suites are provided with this package, such as test_char
,
however you may implement your own by passing a function that returns a
similarly-formatted list.
library(fuzzr)
str(test_char())
#> List of 8
#> $ char_empty : chr(0)
#> $ char_single : chr "a"
#> $ char_single_blank : chr ""
#> $ char_multiple : chr [1:3] "a" "b" "c"
#> $ char_multiple_blank: chr [1:4] "a" "b" "c" ""
#> $ char_with_na : chr [1:3] "a" "b" NA
#> $ char_single_na : chr NA
#> $ char_all_na : chr [1:3] NA NA NA
Evaluate a function argument by supplying fuzz_function
its quoted
name, the tests to run, along with any other required static values.
fuzz_function
returns a fuzz_results
object that stores conditions
raised by a function (message, warning, or error) along with any value
returned by that
function.
fuzz_results <- fuzz_function(fun = lm, arg_name = "subset", data = iris,
formula = Sepal.Length ~ Petal.Width + Petal.Length,
tests = test_all())
#> Warning: `cross_n()` is deprecated; please use `cross()` instead.
#> Warning: `cross_n()` is deprecated; please use `cross()` instead.
#> Warning: at_depth() is deprecated, please use `modify_depth()` instead
You can render these results as a data frame:
fuzz_df <- as.data.frame(fuzz_results)
knitr::kable(head(fuzz_df))
subset | data | formula | output | messages | warnings | errors | result_classes | results_index |
---|---|---|---|---|---|---|---|---|
char_empty | iris | Sepal.Length ~ Petal.Width + Petal.Length | NA | NA | NA | 0 (non-NA) cases | NA | 1 |
char_single | iris | Sepal.Length ~ Petal.Width + Petal.Length | NA | NA | NA | 0 (non-NA) cases | NA | 2 |
char_single_blank | iris | Sepal.Length ~ Petal.Width + Petal.Length | NA | NA | NA | 0 (non-NA) cases | NA | 3 |
char_multiple | iris | Sepal.Length ~ Petal.Width + Petal.Length | NA | NA | NA | 0 (non-NA) cases | NA | 4 |
char_multiple_blank | iris | Sepal.Length ~ Petal.Width + Petal.Length | NA | NA | NA | 0 (non-NA) cases | NA | 5 |
char_with_na | iris | Sepal.Length ~ Petal.Width + Petal.Length | NA | NA | NA | 0 (non-NA) cases | NA | 6 |
You can also access the value returned by any one test by matching the argument tested with its test name:
model <- fuzz_value(fuzz_results, subset = "int_multiple")
coefficients(model)
#> (Intercept) Petal.Width Petal.Length
#> 0.8 NA 3.0
Multiple-argument tests
Specify multiple-argument tests with p_fuzz_function
, passing a named
list of arguments and tests to run on each. p_fuzz_function
will test
every combination of argument and
variable.
fuzz_p <- p_fuzz_function(agrep, list(pattern = test_char(), x = test_char()))
#> Warning: `cross_n()` is deprecated; please use `cross()` instead.
#> Warning: `cross_n()` is deprecated; please use `cross()` instead.
#> Warning: at_depth() is deprecated, please use `modify_depth()` instead
length(fuzz_p)
#> [1] 64
knitr::kable(head(as.data.frame(fuzz_p)))
pattern | x | output | messages | warnings | errors | result_classes | results_index |
---|---|---|---|---|---|---|---|
char_empty | char_empty | NA | NA | NA | invalid ‘pattern’ argument | NA | 1 |
char_single | char_empty | NA | NA | NA | NA | integer | 2 |
char_single_blank | char_empty | NA | NA | NA | ‘pattern’ must be a non-empty character string | NA | 3 |
char_multiple | char_empty | NA | NA | argument ‘pattern’ has length > 1 and only the first element will be used | NA | integer | 4 |
char_multiple_blank | char_empty | NA | NA | argument ‘pattern’ has length > 1 and only the first element will be used | NA | integer | 5 |
char_with_na | char_empty | NA | NA | argument ‘pattern’ has length > 1 and only the first element will be used | NA | integer | 6 |