I agree with the latter parts of your comment, but not that "What makes unit tested code maintainable has nothing to do with how application code is structured".
My original point was that code that's hard to test is often hard to refactor.
My original point was that code that's hard to test is often hard to refactor.
I agree with that. The poster I was replying to said somewhat the opposite. He said:
> Making that code unit testable would have complicated it, thus lowering its maintainability
My basic point was that less complicated doesn't mean maintainable. There's no perfect design in the face of future changes in requirements. So the most important quality of the code we write today is the ability to refactor it and know that it still satisfies all the initial requirements that haven't changed. Unit tests give you that property, lack of complexity doesn't. Simple code can be better than complex, but it's a secondary concern to a comprehensive test suite. I'll take a full test suite over code quality any day because it allows me to go in and add the quality later without fear of breaking things.
I guess I misspoke when I said "how the application is structured" since it you've interpreted it differently than I meant it. It was a reference to the line I quoted above...that complicating code lowers it's maintainability. I just meant that complexity and tested are separate concerns and that tests more so than simplicity make code maintainable. So I think we agree more than we disagree.
> There's no perfect design in the face of future changes in requirements. So the most important quality of the code we write today is the ability to refactor it and[…]
I take issue with the idea of such protean requirements. I'm more the YAGNI type: those changes you're trying to anticipate? They likely won't happen. I'd rather keep the code simple, and add the flexibility only when needed. Simple code is easier to modify anyway.
(Of course, I'd rather not ossify an architecture if I can avoid it, but an ossified architecture is often the sign of tight couplings, which to me are a form of complexity. If we keep the interfaces between modules small and simple, we are more likely to end up with something flexible.)
Read my above point about the cartesian product of tests...if you're doing this, you're almost certainly not getting particularly good coverage of edge cases even if your test coverage percentage is high. If I have test A1, A2, A3 that use a mocked B and B1, B2, B3 that use a mocked C and C1, C2, C3, I've essentially tested 27 different cases that you'd have to write in your hard-coded dependency style while writing only 9 tests. When an application reaches even a moderate amount of complexity and that dependency graph grows beyond 3, that ability for unit tests to cover a geometrically-increasing number of ways that the software behaves is going to be hard to overcome with integration tests like you seem to have been writing. But, again, maybe your dependency graph wasn't big enough to need this. Maybe there was some other mitigating factor that made your situation different. I don't want to speculate on any individual situation since I haven't seen the code and there's no universally correct answer.
> I'm more the YAGNI type: those changes you're trying to anticipate? They likely won't happen.
The one virtually certain thing about the future is that there will be change. Of course you mostly can't predict what will change, but you can be damn near certain that something will. YAGNI is not about predicting that nothing will ever change, it's only about avoiding guessing at what will. Tests on current functionality are not guessing about what will change. The whole point of a test suite is that it avoids ossification. What can be less rigid than something that can easily be pulled apart and put back together in some other form while being sure that it still works? Simple and flexible without that property of safe reorganization is still a landmine waiting to go off in the face of future change.
I used property based tests. With relatively little effort, I ran thousands of tests. Allow me to laugh at your measly 27 from atop my high horse.
More seriously, though, I don't know how I could have mocked my ring buffer without writing another full featured ring buffer. Mocking looks a bit ridiculous in this case. Same for the queue. And the reason why this is so is not tight coupling. It's because my queue relied on the functionality provided by the ring buffer, and my reactor relied on the functionality provided by the queue. If this wasn't the case, I would have written a simpler ring buffer and queue to begin with.
Also, why mock stuff when I can test my code under real conditions?
> The whole point of a test suite is that it avoids ossification.
This feels backwards. If you just mean that test suites prevent the unintended consequences of change, sure. They're like a home made type system in that respect. But if you suggest we should bend a code base just to make it "let's mock everything" testable™, then no. Don't mock stuff for the sake of it, it's a wast of time.
I'd rather concentrate on making the code usable in the first place. With small, well defined interfaces. In my experience, such designs are naturally testable.
> Allow me to laugh at your measly 27 from atop my high horse
If you're going make snide comments, I'll stop this discussion. Suffice it to say you missed the point. 27 isn't just a number, it's a number arrived at by applying an exponent. Exponents get really big in a hurry. As the author of a crypto suite, I'd expect you to pay exponents a bit more respect. Testing 3 different cases per dependency gives you 27. Testing 10 gives you 1000. Property based testing is not a substitute for this kind of coverage. It is, however, complementary. It allows you to increase the base number which is raised to the exponent.
> I could have mocked my ring buffer without writing another full featured ring buffer. Mocking looks a bit ridiculous in this case.
It's safe to assume from this comment that you don't really understand mocking. Mocks aren't an implementation of an interface to be used in tests. Mocks verify that they were called in an expected way/order and give back the appropriate value. They don't actually do anything. They're highly coupled with each test case. This is why most mocking frameworks dynamically generate the mock per-test and let you simply verify the call(s) and tell it what to return.
> This feels backwards
It's absolutely not backwards. The main purpose of a test suite is to find a very specific type of bug...regressions. It's not to avoid other sorts of bugs other than the fact that forcing developers to write tests will force them to think about their code in ways that make them realize they missed something during implementation.
But the most important thing is to be able to rely on them to tell you when you've broken something that previously worked. Every single time I've come to a code base that was either missing tests or relied too heavily on integration tests, we've had a significant problem with regressions and, over time, developers shied away from making significant changes to the code base because they were afraid to break it. And the result is that ossification that you try not to achieve. But when you see a code base with a commitment to unit tests, you also see one where developers are free to make the necessary radical changes without fear of breaking existing functionality. They make the changes, run the suite and let it tell them everywhere they forgot to change, whether that be in application code or test code.
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Yeah, C++. I don't know of any mocking framework there, and I'm not going to look for one —my current opinion on that stuff veers towards "worse than useless". (You just reinforced that notion by the way, see below.)
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27 is a number you arrived by fantasizing about how mocking make your tests more thorough than they actually are —and you're not even testing under real conditions! Just an outsider's scepticism.
Your exponent is also driven by the number of dependencies, whose increasing number requires an exponentially growing number of tests. Property based testing on the other hand (search for "QuickCheck") generates as many random tests as one feels like using. (Of course, one has to test for several properties, but then each property can be thoroughly tested.)
> It's safe to assume from this comment that you don't really understand mocking.
Indeed, thanks for the explanation. But that just showed mocs are fundamentally incompatible with property based testing: I'd need to generate a moc for each random test case. Nope. I'm keeping my property based tests, they're much more powerful.
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So you were talking about using your test suite like a type system on steroids. Good. Just keep in mind that there's a stark difference between maintaining a good test suite, and bending the code around some narrow idea of testability. I only do the former. Oh, and I tend to write tests after I write the code. Property based test don't make sense before the module is done anyway.
A quick note about unit vs integration test: in our little A->B->C example, testing C, then B (without mocs), then A (without mocs) are all unit tests in my book. A few internal dependencies aren't going to change that.
By the way, I'm talking about compile-time dependency, of the kind that don't involve runtime shared state. Shared state open a whole 'nother can of worm, and I do see the need to separate unit and integration tests for those. (I also see the need to avoid shared state as much as possible.)
Incidentally, here's two C++ mocking frameworks found from Google, in case you're more open minded than I'm giving you credit for:
https://github.com/google/googletest/tree/master/googlemock (part of https://github.com/google/googletest)
Here's a primer: you think of some property that must hold for your object. Take a ring buffer for instance: if you push N elements, it must be of size N (assuming it's capacity is N or more). Then you generate random input, and use it to test your property. One property, thousands of tests. Once that's done, you can move on to some other property (like, the ring buffer must have FIFO behaviour).
> to declare something as popular and influential as those two concepts "worse than useless" without bothering to understand them is, well, ballsy.
It wouldn't be the first time our industry demonstrated blatant inadequacy —at least in hindsight. We're still a young field, popularity doesn't mean much. Maybe I would have considered mocking if I didn't know of property based testing. But the power difference between singular unit testing an property based tests is too great to ignore.
The reason I call mocking frameworks "worse than useless" is because they turn you away from property based tests. If they were at least compatible with them… I'll allow one exception: if you can use the same mock with all the random input, or at least easily generate a moc per random input, then it wouldn't be too bad.
It wouldn't be too good either, though. I'd rather test with the real stuff. If there's a regression, it will be revealed, with or without mocking. Actually, if some dependency isn't properly tested (distracted dev or something), not mocking it gives you a second chance at detecting bugs. On the other hand, have you ever seen a regression that would have gone undetected if you didn't used mocking? That doesn't seem plausible.
The only use I see for mocks is to track down bugs once they are detected —by narrowing the search space. But I've never needed it in practice, with one possible exception: Lua.
Are you using dynamic typing? That would explain a lot.
Choosing to write unit tests instead of integration tests does not preclude the use of property based testing or any other technique that covers how you test code. As I stated before, if you were to use property based testing at the unit test level, it would be all the more powerful because you'd get that same exponential coverage just with significantly larger number of effective tests per unit of code. From the A, B, C dependency graph example, if you used property based testing to test A thousands of times, B thousands of times and C thousands of times, you'd effectively be testing thousands times thousands times thousands (aka billions) of different scenarios. And you'd still be able to use mocks because mocks are created in test code and can be as dynamic as you need them to be.
I've done testing in many languages, both static and dynamic. Dynamic languages, thanks to the lack of static type checking, often don't need a mocking framework because the language is flexible enough that you can swap in a mock-like object at runtime. But the concepts are the same. And there really is a ton of value in testing code you've written in isolation. It's the testing equivalent of separation of concerns. And just like some developers never grok the single responsibility principle, some developers never grok the need to test code in isolation. You've obviously understood how to encapsulate your concerns based on the design you implemented. And yet the testing strategy you described is the opposite...trying to test everything at once rather than focusing on each test covering one specific bit of code.
Me on the other hand could pretend something to this effect. By testing A, B, and C three times each, I effectively test B 6 times, and C 9 times, for a total of 3+6+9=18 "tests". But even then I would hesitate to pull such a number out of my ass, because the extra "free" tests are likely redundant with the real ones down the line. (And if my coverage is any good, those are guaranteed to be redundant).
Surely you don't pretend mocking lets you test more things than my approach? Surely the mocs don't behave any differently than the real thing on the inputs they are given? How come then that my "integration" tests don't supersede your unit tests?
> Choosing to write unit tests instead of integration tests does not preclude the use of property based testing
I assume at this point that your definition of unit test means mocking everything, except perhaps the standard library. You said earlier:
> Mocks verify that they were called in an expected way/order and give back the appropriate value. They don't actually do anything. They're highly coupled with each test case.
So, if tests are generated randomly, mocs must be adapted to each random test, right? Now you need some moc generator, that will generate a moc for each test case. This veers eerily close to actually implementing the interface we were trying to moc.
Now I realise I did miss something:
> Mocks verify that they were called in an expected way/order and give back the appropriate value.
Why would they do that? Oh, I see: we are mocking a mutable object that is used somewhere else. In other words, shared state. The one case for which I understand isolation could be good.
This may all be a big misunderstanding. The A->B->C dependency I was thinking of is pretty simple: C is an implementation detail of B. Each B contains and uses a C, but that C isn't used anywhere else. Thus, mocking B or C would mean testing the implementation details of A, and that is a big no-no —the kind of thing Uncle Bob would call TDD gone wrong.
> And there really is a ton of value in testing code you've written in isolation.
What value exactly? Does isolating objects in the tests make those tests catch more bugs? What kind of bugs? Does isolating objects make detected bugs faster to track down? Does isolating objects in the tests influence how the code is written in the first place? How? Would the test suite run faster?
> And yet the testing strategy you described is the opposite...trying to test everything at once rather than focusing on each test covering one specific bit of code.
Now that's a strawman. I don't test everything at once. If I did, I would merely test A. No no no, I test and debug C first. When I'm confident it is bug-free, I test and debug B. Bugs are easily tracked down, because C is bug free, so if something went wrong it must be B. I only test A last, when I'm confident B and C are both bug-free.