[unit-testing] New to unit testing, how to write great tests?

I'm fairly new to the unit testing world, and I just decided to add test coverage for my existing app this week.

This is a huge task, mostly because of the number of classes to test but also because writing tests is all new to me.

I've already written tests for a bunch of classes, but now I'm wondering if I'm doing it right.

When I'm writing tests for a method, I have the feeling of rewriting a second time what I already wrote in the method itself.
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.

This is just a feeling, and as said earlier, I have no experience of testing. If some more experienced testers out there could give me advices on how to write great tests for an existing app, that would be greatly appreciated.

Edit : I would love to thank Stack Overflow, I had great inputs in less that 15 minutes that answered more of the hours of online reading I just did.

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.

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.

tests are supposed to improve maintainability. If you change a method and a test breaks that can be a good thing. On the other hand, if you look at your method as a black box then it shouldn't matter what is inside the method. The fact is you need to mock things for some tests, and in those cases you really can't treat the method as a black box. The only thing you can do is to write an integration test -- you load up a fully instantiated instance of the service under test and have it do its thing like it would running in your app. Then you can treat it as a black box.

When I'm writing tests for a method, I have the feeling of rewriting a second time what I          
already wrote in the method itself.
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.

This is because you are writing your tests after you wrote your code. If you did it the other way around (wrote the tests first) it wouldnt feel this way.

Don't write tests to get full coverage of your code. Write tests that guarantee your requirements. You may discover codepaths that are unnecessary. Conversely, if they are necessary, they are there to fulfill some kind of requirement; find it what it is and test the requirement (not the path).

Keep your tests small: one test per requirement.

Later, when you need to make a change (or write new code), try writing one test first. Just one. Then you'll have taken the first step in test-driven development.

Try writing a Unit Test before writing the method it is going to test.

That will definitely force you to think a little differently about how things are being done. You'll have no idea how the method is going to work, just what it is supposed to do.

You should always be testing the results of the method, not how the method gets those results.

Unit testing is about the output you get from a function/method/application. It does not matter at all how the result is produced, it just matters that it is correct. Therefore, your approach of counting calls to inner methods and such is wrong. What I tend to do is sit down and write what a method should return given certain input values or a certain environment, then write a test which compares the actual value returned with what I came up with.