Testing code

This section is inspired by Karl Broman’s notes.

You want to test your code, but more importantly, you want to continuously test your code as you introduce more changes (preferably automated testing).

Different types of tests:

• Check inputs
  • Stop if the inputs aren’t as expected.
• Unit tests
  • For each small function: does it give the right results in specific cases?
• Integration tests
  • Check that larger multi-function tasks are working.
• Regression tests
  • Compare output to saved results, to check that things that worked continue working

Check inputs with R package assertthat

You are creating an R function winsorize that limits extreme values of a vector. You want to include some assert_that statements to make sure that the input arguments are what you expect:

#' import assertthat
winsorize <-
function(x, q=0.006)
{
if(all(is.na(x)) || is.null(x)) return(x)
assert_that(is.numeric(x))
assert_that(is.number(q), q>=0, q<=1)
lohi <- quantile(x, c(q, 1-q), na.rm=TRUE)
if(diff(lohi) < 0) lohi <- rev(lohi)
x[!is.na(x) & x < lohi[1]] <- lohi[1]
x[!is.na(x) & x > lohi[2]] <- lohi[2]
x
}

Unit tests with R package testthat

Now, you want to make sure that the winsorize function returns what it is supposed to:

test_that("winsorize works for small vectors", {
x <- c(2, 3, 7, 9, 6, NA, 5, 8, NA, 0, 4, 1, 10)
result1 <- c(2, 3, 7, 9, 6, NA, 5, 8, NA, 1, 4, 1, 9)
result2 <- c(2, 3, 7, 8, 6, NA, 5, 8, NA, 2, 4, 2, 8)
expect_identical(winsorize(x, 0.1), result1)
expect_identical(winsorize(x, 0.2), result2)
})

Integration tests in tests folder

You can store test functions in the tests folder, for example, tests/testthat.R:

library(testthat)
test_check("mypkg")

Automated testing

You can perform automated tests with Codecov within github. Learn more about Codecov here.