Each section provides a function that supposedly works as expected, but quickly proves to misbehave. The exercise aims at first writing some dedicated testing functions that will identify the problems and then update the function so that it passes the specific tests. This practice is called unit testing and we use the RUnit package for this. See the Unit Testing How-To guide for details on unit testing using RUnit.

# Subsetting

## The buggy function

## Example
isIn <- function(x, y) {
sel <- match(x, y)
y[sel]
}

## Expected
x <- sample(LETTERS, 5)
isIn(x, LETTERS)

## Bug!
isIn(c(x, "a"), LETTERS)

## A unit test and a solution

## Unit test:
library("RUnit")
test_isIn <- function() {
x <- c("A", "B", "Z")
checkIdentical(x, isIn(x, LETTERS))
checkIdentical(x, isIn(c(x, "a"), LETTERS))
}

test_isIn()

## updated function
isIn <- function(x, y) {
sel <- x %in% y
x[sel]
}

test_isIn()

# Character matching

## The buggy function

## Example
isExactIn <- function(x, y)
y[grep(x, y)]

## Expected
isExactIn("a", letters)

## Bugs
isExactIn("a", c("abc", letters))
isExactIn(c("a", "z"), c("abc", letters))

# If conditions with length > 1

## The buggy function

## Example
ifcond <- function(x, y) {
if (x > y) {
ans <- x*x - y*y
} else {
ans <- x*x + y*y
}
ans
}

## Expected
do(3, 2)
do(2, 2)
do(1, 2)

## Bug!
do(3:1, c(2, 2, 2))

## The function

## Example
distances <- function(point, pointVec) {
x <- point[1]
y <- point[2]
xVec <- pointVec[,1]
yVec <- pointVec[,2]
sqrt((xVec - x)^2 + (yVec - y)^2)
}

## Expected
x <- rnorm(5)
y <- rnorm(5)

m <- cbind(x, y)
p <- m[1, ]

distances(p, m)

## Bug!
dd <- data.frame(x, y)
q <- dd[1, ]

distances(q, dd)

# Iterate on 0 length

## The buggy function

## Example
sqrtabs <- function(x) {
v <- abs(x)
sapply(1:length(v), function(i) sqrt(v[i]))
}

## Expected
all(sqrtabs(c(-4, 0, 4)) == c(2, 0, 2))

## Bug!
sqrtabs(numeric())