If a particular test never finds a bug in its lifetime (and isn't used as documentation either), you might as well as not have written it, and the time would be better spent on something else instead--like a new feature or a different test.
Of course, you don't know ahead of time exactly which tests will catch bugs. But given finite time, if one category of test has a higher chance of catching bugs per time spent writing it, you should spend more time writing that kind of test.
Getting back to unit tests: if they frequently need to be rewritten as part of refactoring before they ever catch a bug, the expected value of that kind of test becomes a fraction of what it would be otherwise. It tips the scales in favor of a higher-level test that would catch the same bugs without needing rewrites.
> If a particular test never finds a bug in its lifetime (and isn't used as documentation either), you might as well as not have written it
That's like saying you shouldn't have installed fire alarms because you didn't wind up having a fire. Also, tests can both 1) help you write the code initially and 2) give a sense of security that the code is not failing in certain ways.
> It tips the scales in favor of a higher-level test that would catch the same bugs without needing rewrites.
Writing higher level tests that catch the same bugs as smaller, more focused tests is harder, likely super-linearly harder. In my experience, you get far more value for your time by combining unit, functional, system, and integration tests; rather than sticking to one type because you think it's best.
My comment went on to say that you don't know ahead of time exactly which tests will prove useful. So you can't just skip writing them altogether. They key point is that if you have evidence ahead of time that a whole class of tests will be less useful than another class (because they will need several rewrites to catch a similar set of bugs) that fact should inform where you spend your time.
To go with the fire alarm analogy and exaggerate a little, it would work like this: you could attempt to install and maintain small disposable fire alarms in the refrigerator as well as every closet, drawer, and pillowcase. I'm not sure if these actually exist, but let's say they do. You then have to keep buying new ones since the internal batteries frequently run out. Or, you could deploy that type mainly in higher-value areas where they're particularly useful (near the stove), and otherwise put more time and money in complete room coverage from a few larger fire alarms that feature longer-lasting batteries. Given that you have an alarm for the bedroom as a whole, you absolutely shouldn't waste effort maintaining fire alarms in each pillowcase, and the reason is precisely that they won't ever be useful.
There are side benefits you mentioned to writing unit tests, of course, like helping you write the API initially. There are other ways to get a similar effect, though, and if those provide less benefit during refactoring but you still have to pay the cost of rewriting the tests, that also lowers their expected value.
To avoid misunderstanding, I also advocate a mixture of different types of tests. My comment is that based on the observation that unit tests depending on change-prone internal APIs tend to need more frequent rewrites, that fact should lower their expected value, and therefore affect how the mixture is allocated.
I get what you're saying and it makes sense to me.
> unit tests depending on change-prone internal APIs
This in particular is worth highlighting. I tend to now write unit tests for things that are getting data from one place and passing it another, unless the code is complex enough that I'm worried it might not work or will be hard to maintain. And generally, I try to break out the testable part to a separate function (so it's get data + manipulate (testable) + pass data).
Of course, you don't know ahead of time exactly which tests will catch bugs. But given finite time, if one category of test has a higher chance of catching bugs per time spent writing it, you should spend more time writing that kind of test.
Getting back to unit tests: if they frequently need to be rewritten as part of refactoring before they ever catch a bug, the expected value of that kind of test becomes a fraction of what it would be otherwise. It tips the scales in favor of a higher-level test that would catch the same bugs without needing rewrites.