New to unit testing, how to write great tests?
It's worth noting that retro-fitting unit tests into existing code is far more difficult than driving the creation of that code with tests in the first place. That's one of the big questions in dealing with legacy applications... how to unit test? This has been asked many times before (so you may be closed as a dupe question), and people usually end up here:
Moving existing code to Test Driven Development
I second the accepted answer's book recommendation, but beyond that there's more information linked in the answers there.
For unit testing, I found both Test Driven (tests first, code second) and code first, test second to be extremely useful.
Instead of writing code, then writing test. Write code then look at what you THINK the code should be doing. Think about all the intended uses of it and then write a test for each. I find writing tests to be faster but more involved than the coding itself. The tests should test the intention. Also thinking about the intentions you wind up finding corner cases in the test writing phase. And of course while writing tests you might find one of the few uses causes a bug (something I often find, and I am very glad this bug did not corrupt data and go unchecked).
Yet testing is almost like coding twice. In fact I had applications where there was more test code (quantity) than application code. One example was a very complex state machine. I had to make sure that after adding more logic to it, the entire thing always worked on all previous use cases. And since those cases were quite hard to follow by looking at the code, I wound up having such a good test suite for this machine that I was confident that it would not break even after making changes, and the tests saved my ass a few times. And as users or testers were finding bugs with the flow or corner cases unaccounted for, guess what, added to tests and never happened again. This really gave users confidence in my work in addition to making the whole thing super stable. And when it had to be re-written for performance reasons, guess what, it worked as expected on all inputs thanks to the tests.
All the simple examples like function square(number)
is great and all, and are probably bad candidates to spend lots of time testing. The ones that do important business logic, thats where the testing is important. Test the requirements. Don't just test the plumbing. If the requirements change then guess what, the tests must too.
Testing should not be literally testing that function foo invoked function bar 3 times. That is wrong. Check if the result and side-effects are correct, not the inner mechanics.
My tests just seems so tightly bound to the method (testing all codepath, expecting some inner methods to be called a number of times, with certain arguments), that it seems that if I ever refactor the method, the tests will fail even if the final behavior of the method did not change.
I think you are doing it wrong.
A unit test should:
- test one method
- provide some specific arguments to that method
- test that the result is as expected
It should not look inside the method to see what it is doing, so changing the internals should not cause the test to fail. You should not directly test that private methods are being called. If you are interested in finding out whether your private code is being tested then use a code coverage tool. But don't get obsessed by this: 100% coverage is not a requirement.
If your method calls public methods in other classes, and these calls are guaranteed by your interface, then you can test that these calls are being made by using a mocking framework.
You should not use the method itself (or any of the internal code it uses) to generate the expected result dynamically. The expected result should be hard-coded into your test case so that it does not change when the implementation changes. Here's a simplified example of what a unit test should do:
testAdd()
{
int x = 5;
int y = -2;
int expectedResult = 3;
Calculator calculator = new Calculator();
int actualResult = calculator.Add(x, y);
Assert.AreEqual(expectedResult, actualResult);
}
Note that how the result is calculated is not checked - only that the result is correct. Keep adding more and more simple test cases like the above until you have have covered as many scenarios as possible. Use your code coverage tool to see if you have missed any interesting paths.