In his 1972 essay “The Humble Programmer,” Edsger W. Dijkstra said that “Program testing can be a very effective way to show the presence of bugs, but it is hopelessly inadequate for showing their absence.” That doesn’t mean we shouldn’t try to test as much as we can!
Correctness in our programs is the extent to which our code does what we intend it to do. Rust is designed with a high degree of concern about the correctness of programs, but correctness is complex and not easy to prove. Rust’s type system shoulders a huge part of this burden, but the type system cannot catch every kind of incorrectness. As such, Rust includes support for writing automated software tests within the language.
As an example, say we write a function called add_two that adds 2 to whatever
number is passed to it. This function’s signature accepts an integer as a
parameter and returns an integer as a result. When we implement and compile
that function, Rust does all the type checking and borrow checking that you’ve
learned so far to ensure that, for instance, we aren’t passing a String value
or an invalid reference to this function. But Rust can’t check that this
function will do precisely what we intend, which is return the parameter plus 2
rather than, say, the parameter plus 10 or the parameter minus 50! That’s where
tests come in.
We can write tests that assert, for example, that when we pass 3 to the
add_two function, the returned value is 5. We can run these tests whenever
we make changes to our code to make sure any existing correct behavior has not
changed.
Testing is a complex skill: although we can’t cover every detail about how to write good tests in one chapter, we’ll discuss the mechanics of Rust’s testing facilities. We’ll talk about the annotations and macros available to you when writing your tests, the default behavior and options provided for running your tests, and how to organize tests into unit tests and integration tests.