I highly recommend reading Michael Feather's Working Effectively with Legacy Code. He has the best description of unit tests that I've seen. Briefly, he describes it like a clamp. When you are working on a wood working project, you clamp part of your project so that it doesn't move. Then you work on the bit you are interested in. Later you clamp that part and work on another part. The purpose of unit tests is not to test the behaviour (unfortunate nomenclature aside) -- it's to immobilise it. This allows you to work on another part of the the system and be alerted if you've caused something to slip.

Acceptance tests are incredibly important. They tell you if the system is working. No amount of unit tests are going to help you with that. Once you have accepted the behaviour, what you're really interested in is whether or not the behaviour has changed. You do not need your acceptance tests for that -- your unit tests will tell you.

I'll write it a bit more concisely because I think it is important: acceptance tests tell you whether or not the code is working correctly. Unit tests tell you whether or not the code is doing the same thing it was doing the last time you ran the tests.

The reason I don't favour a large suite of acceptance tests is because they are unwieldy. It's fine for a few months, but once you get a few tens of thousands of lines of code, you will end up with a lot of acceptance tests. These acceptance tests are extremely hard to refactor. It's extremely hard to remove duplication. Over time, they get more and more problematic until you are spending more time trying to figure out how to make your acceptance tests pass than you are trying to figure out how to make your production changes.

Unit tests, when written in specific ways, have less problem with this. Some people think about a "unit" as being a class. But really a "unit" is anything that you might want to isolate in your clamp. It can be a function. It can be a class. It can be a module. Your unit tests should probe the behaviour in the unit (and by "probe" I mean, expose the internal state). Michael Feather's has a great analogy of a "seam" which runs through your code. You try to find (or make) that seam and you insert probes to show you the state in various circumstances.

IMHO, you should write unit tests the exact same way you write any code. Your "circumstances" (or scenarios, I guess) consist of creating the data structures to give your initial state. Your "tests" consist of probing the state along the seams and comparing it to expected values. This is simple code. You should be able to maintain this code using the same tools you use to maintain any code. You should write functions. You should write classes. You should write modules. You should use all the tricks of your trade to reduce the complexity of your "test" code. Your goal is to create specificity when tests "fail" (the probe detects behaviour different than your expectation -- or the clamp detects that your wood has slipped). When behaviour changes, only a few tests (ideally one) should "fail". It should report the "failure" in a way that immediately describes the difference between the state you expected and the state that you probed. It should be easy to change the probe when the behaviour is intentionally changed (ideally changing only one place). It should be easy to probe new behaviour (just build your data and add an expectation). Finally, it should be easy to reason about the behaviour of the code by reading the "tests". Refactoring your tests and removing duplication is very important here.

As for acceptance tests, like I said, they are incredibly important. What I don't find particularly useful is a large suite of regression acceptance tests. The unit tests already tell me when the behaviour has changed. When written well, they even tell me exactly where in the code the behaviour "slipped". I often write manual acceptance tests. Once I have tested it, it is not necessary to test it again (as long as I have a good unit test suite).

My personal opinion as to why people find automated acceptance tests suites important is because they have never worked with a good unit test suite before. There is a general lack of experience in the industry with these concepts. Quite a few people's experience with well tested code is with green field projects. Often these people leave after a year or so. It's not until you have a lot of experience working with the legacy of various testing techniques that you can understand the advantages and disadvantages. I think this is why Michael Feathers is so respected -- as far as I can tell he specialises in legacy code.

Having said all that (and I'll be surprised if you make it to the bottom :-) ), I do value a small automated acceptance test suite. It's my canary in the mine. If it ever fails, then I know I've really stuffed something up and I launch an immediate investigation. Also, there are some things that can't be unit tested effectively (for example testing a web application across both client and server) -- you end up faking the boundaries, which leads to the possibility of skewing. Again, in those cases, I try to find a few end to end tests that will hit the majority possible problems.

I hope you found that interesting. I've typed up essentially this same message in at least 10 different threads of the past couple of years. I think it's slowly getting better, but I think I still haven't managed to explain the concepts as well as they need to be explained. If you've made it this far, thanks for reading :-)