Kotlin Code Smell 34 - Fragile Tests
Tests are our safety net. When their integrity is in doubt, we're at risk
Table of contents
TL;DR: Steer clear of non-deterministic tests..
Problem
Lack of determinism
Eroding confidence
Time squandered
Solution
Ensure that the test is fully deterministic. Eradicate any potential for unpredictable behavior.
Eliminate test coupling.
Examples
The terms "Fragile," "Intermittent," "Sporadic," and "Erratic" are often used interchangeably when discussing problematic tests in many development environments.
However, such tests erode the trust developers place in their test suites.
Such tests are best avoided.
Sample Code
Wrong
import org.junit.jupiter.api.Assertions.assertEquals
import org.junit.jupiter.api.Test
abstract class SetTest {
protected abstract fun constructor(): MutableSet<String>
@Test
fun `test add empty`() {
val set = constructor()
set.add("green")
set.add("blue")
assertEquals("[green, blue]", set.toString())
// This is fragile since the outcome hinges on the set's
// ordering, which isn't predefined and can vary based on
// the set's implementation.
}
}
Right
import org.junit.jupiter.api.Test
import kotlin.test.assertEquals
import kotlin.test.assertTrue
abstract class SetTest {
protected abstract fun constructor(): MutableSet<String>
@Test
fun `test add empty`() {
val set = constructor()
set.add("green")
assertEquals("[green]", set.toString())
}
@Test
fun `test entry at single entry`() {
val set = createFromArgs("red")
val result = set.contains("red")
assertTrue(result)
}
}
Conclusion
Fragile tests often indicate system coupling and manifest as non-deterministic or unpredictable behaviors.
Addressing and resolving these erratic tests can drain considerable developer time and energy.