Unit tests - The benefit from unit tests with contract changes?

Question

Recently I had an interesting discussion with a colleague about unit tests. We were discussing when maintaining unit tests became less productive, when your contracts change.

Perhaps anyone can enlight me how to approach this problem. Let me elaborate:

So lets say there is a class which does some nifty calculations. The contract says that it should calculate a number, or it returns -1 when it fails for some reason.

I have contract tests who test that. And in all my other tests I stub this nifty calculator thingy.

So now I change the contract, whenever it cannot calculate it will throw a CannotCalculateException.

My contract tests will fail, and I will fix them accordingly. But, all my mocked/stubbed objects will still use the old contract rules. These tests will succeed, while they should not!

The question that rises, is that with this faith in unit testing, how much faith can be placed in such changes... The unit tests succeed, but bugs will occur when testing the application. The tests using this calculator will need to be fixed, which costs time and may even be stubbed/mocked a lot of times...

How do you think about this case? I never thought about it thourougly. In my opinion, these changes to unit tests would be acceptable. If I do not use unit tests, I would also see such bugs arise within test phase (by testers). Yet I am not confident enough to point out what will cost more time (or less).

Any thoughts?

Answer 1

It's better to have to fix unit test that fail due to intentional code changes than not having tests to catch the bugs that are eventually introduced by these changes.

When your codebase has a good unit test coverage, you may run into many unit test failures that are not due to bugs in the code but intentional changes on the contracts or code refactoring.

However, that unit test coverage will also give you confidence to refactor the code and implement any contract changes. Some test will fail and will need to be fixed, but other tests will eventually fail due to bugs that you introduced with these changes.

Answer 2

The first issue you raise is the so-called "fragile test" problem. You make a change to your application, and hundreds of tests break because of that change. When this happens, you have a design problem. Your tests have been designed to be fragile. They have not been sufficiently decoupled from the production code. The solution is (as it it in all software problems like this) to find an abstraction that decouples the tests from the production code in such a way that the volatility of the production code is hidden from the tests.

Some simple things that cause this kind of fragility are:

• Testing for strings that are displayed. Such strings are volatile because their grammar or spelling may change at the whim of an analyst.
• Testing for discrete values (e.g. 3) that should be encoded behind an abstraction (e.g. FULL_TIME).
• Calling the same API from many tests. You should wrap the API call in a test function so that when the API changes you can make the change in one place.

Test design is an important issue that is often neglected by TDD beginners. This often results in fragile tests, which then leads the novices to reject TDD as "unproductive".

The second issue you raised was false positives. You have used so many mocks that none of your tests actually test the integrated system. While testing independent units is a good thing, it is also important to test partial and whole integrations of the system. TDD is not just about unit tests.

Tests should be arranged as follows:

• Unit tests provide close to 100% code coverage. They test independent units. They are written by programmers using the programming language of the system.
• Component tests cover ~50% of the system. They are written by business analysts and QA. They are written in a language like FitNesse, Selenium, Cucumber, etc. They test whole components, not individual units. They test primarily happy path cases and some highly visible unhappy path cases.
• Integration tests cover ~20% of the system. They tests small assemblies of components as opposed to the whole system. Also written in FitNesse/Selenium/Cucumber etc. Written by architects.
• System tests cover ~10% of the system. They test the whole system integrated together. Again they are written in FitNesse/Selenium/Cucumber etc. Written by architects.
• Exploratory manual tests. (See James Bach) These tests are manual but not scripted. They employ human ingenuity and creativity.