This is actually one of the bigger 'problems' with {T,B}DD; it's much harder to figure out how much time it takes to complete things.
BDD: Wrote the test, wrote the feature, checked it in, wall clock time, 1 hour. Next week, something unrelated changes, my tests show right where the problem is, 10 minute fix. Total time: 1:10.
No testing: wrote the feature, half an hour. Next week, something unrelated changes, breaks the feature, spend an hour fixing it. Total time: 1:30. And keep adding time when other things break later, too...
In projects with a high test coverage, I almost never spend any time debugging. That doesn't mean it's easy to recognize the saved time, though.
TDD: Spend an hour writing the test (sometimes more if I have to figure out how to properly work with a third-party library). Spend 10 minutes writing the code. Decide a few days later that I need to rework the API a bit on the feature, so spend another hour rewriting tests and 5 minutes writing new production code.
No testing: Write the feature, 20 minutes. "Test" while writing it (refresh a web page or run something at the CL). Realize a few days later I need to rework things, spend 10 minutes doing so. In the rare instances where something breaks, spend 20 or 30 minutes tracking it down and fixing.
Don't read this as an argument against TDD. It's more that I have a very hard time actually realizing an increase in productivity or code quality when using it. TDD-backed code generally takes me longer to write and pretty much nobody on the business team I report to notices any difference whatsoever, except that feature X took a week longer than it probably would have otherwise. The few bugs that do creep into production code are usually dealt with promptly, and I'm not sure TDD would result in entirely bug-free code either way.
Anyhow, that's why this conversation has been quite valuable to me. I am convinced that if I can clear away real-world obstacles in TDD I can do a better job of embracing it and realizing the productivity benefits that everyone always crows about. For now, my personal experience is that it's a means to marginally improve code quality at a high cost of time.
I write unit tests so I don't have to refresh web pages all day. If I do find myself going to the command-line to test something, I figure out what I'm trying to test, and write a unit test instead; it's something I have missed when I was writing the upfront tests. Then I can do it again, and again, and again, and use continuous integration so it runs those tests for me over and over.
If you do a lot of web dev, Selenium is a really good way of testing web page features.
I have the same problem as the parent and this is exactly why. I've always thoroughly tested everything but with ad hoc tests that I had to do over and over.
The main thing I miss with TDD is the interactive nature. If I'm testing in Smalltalk I can write code right inside the debugger and watch the effect it has, but TDD always moves me back to what Smalltalkers call "cult of the dead" programming where I have to stop, run the tests and wait for the output. I wish there was a way to make it more interactive. It would be easier to force myself to do it then.
This. And also Refactoring is almost a dirty word so we try to keep it to ourselves and sneak in bits of refactoring when implementing bigger features
I also have the pleasure of writing 90% of my code in Ruby, which has top notch testing support basically everywhere.
This way manual testing becomes automated tests with very minimal additional effort.
Also, by writing the test first, you ensure that the code is actually easy to test. This gets easier as you get more experienced with testing, but still.
I don't write as many tests as you do though, Steve. I generally stop once I have the nominal test cases in place, I don't test edge cases. They seem to tend to get hit by upstream unit tests anyway (I don't mock except where it is absolutely necessary). If I do hit a difficult-to-find bug, I use tests as one of my main debugging tools, writing tests for any code for which I have some doubts. By the end of a project, I generally have a fairly high code coverage for my tests, but I never feel like I'm just writing them for the methodology - they are either testing the nominal case, or testing to verify behaviour when tracking down a bug
I totally forgot about this, but I agree 100%. I'm a big fan of "Write this as though the underlying code exists, then fill it out" for API design.
I don't write as many tests as you'd think I do, actually, because I heavily favor integration tests over unit-style tests, and so we're probably much closer in that regard than you think. ;)
So generally you need to try to find a small enough product so you can build it using TDD. Also stay as simple as you can with your testing - even if it feels very repetitive. I'm only now thinking of adding more tools to my testing toolchain after I have a better understanding of the actual problems I run into often.
About testing web APIs. You need both unit and system tests. The unit tests make sure your internal processing is solid. The system tests will directly make calls to the service. That won't always feel pretty, but it's the best way to approach it IMO.
Edit: I know this may not be applicable in transloadit's case. I'm asking for a general strategy
But anyway, I am no expert on this so I can't give you solid advice.
If you're testing javascript, you'll need to use Selenium or something similar.
Your responses illustrate a different perspective, that testing is cheap (this probably comes with experience, I would imagine). Anyhow, I can see that if I thought of tests as cheap, I wouldn't get so hung up on my tests breaking when I change direction on a feature.
I also write a fair amount of code that consumes web APIs, so I have lost a lot of hair figuring out to test against those properly without mocking out everything to the point of meaninglessness.