Over the past couple of years or so, I’ve started to come to the opinion that reliance on mocks for driving out design can seriously hamper large- to medium-scale refactoring efforts. Things like adding method parameters, renames and the like aren’t affected. But many of the techniques in Refactoring and Refactoring to Patterns become quite difficult to do when our tests are overly concerned with the implementation details of our system under test.
Before I get to the punch line, it might be worth setting up the context of how I got here. Up until of a couple of years ago, I had written my unit tests in a very top-down, one-layer-at-a-time approach. I’d do some whiteboarding, figure out what my top-level component looked like through tests, and built interfaces and mocked out interactions with lower-level components. At no point was I testing the top-level component using the actual low-level component.
Two things started to influence my testing strategies away from that notion. One was experience trying to do large refactorings, where I was pulling out cross-cutting concerns across an entire layer of the system. At that point, all my unit tests with all their mocks were a large barrier to these design changes. The tests were concerned with low-level interactions between components. But at this level of refactoring, those interactions were about to get deleted, but I still had interesting parts of those tests I wanted to keep. Namely, the direct inputs and outputs of the component, and I could give a flying [bleep] about the indirect inputs and outputs.
At some point, I wanted a test that only concerned itself with observable results.
Shift towards BDD
Following the talks and guidance from Scott Bellware, I started writing more tests in the Context-Specification style of tests. That is, combining testcase-class-per-fixture and a naming style that focused on describing the behavior of the system from a user’s point of view (though who that user might be would change depending on the perspective).
At that point, talking about the interactions of between dependencies became less interesting. Specifically, because I found that except for unobservable indirect outputs (sending an email, webservices and the like), the language centered around things that I could observe.
If implementation detail language was removed from the test names, I found myself far more concerned about how the real system behaved. When test names and code were then using the real component and its real dependencies, I found myself far more amenable to making big sweeping changes in responsibilities, because at every level, I was describing the behavior of the direct, observable behavior.
Observing indirect outputs
Indirect outputs (a void method) are usually tested in a mocking framework by either setting an expectation that the method will be called, or asserting afterwards that the method WAS called. But what if the real component was used? The method was called in order to affect a change in something, that’s the whole point of commands. Commands are intended to induce a side effect, it’s now just up to us to observe it.
For unit tests, I draw the line here when the request crosses the process boundary (database, queue etc). However, I’ll still build full-system tests that do perform a command and directly observe all that there is to observe (granted that I actually own the observable systems). If I don’t own that system that I can observe, that’s usually when our partners complain that I’m calling their tests systems too often and please stop.
When building out the components, I still do things like program to interfaces, as it still helps me build out a component’s shape without worrying about an implementation yet. In the test, I’ll use a container to instantiate the components, only filling in process-crossing components with mocks.
Supplying indirect inputs
Indirect inputs are dependencies whose methods that are called return a value. Same as indirect outputs – if the component crosses a process boundary, I’ll supply a fake or a stub. In integration tests, I’ll supply the real component if it’s a system I own, otherwise I’ll keep the fake or stub.
Side note – I’m not a fan of committing always-running tests that hit systems I don’t own. I don’t want a failed build because someone else’s test system isn’t up.
If it becomes difficult to set up these inputs, there are patterns for that. Whether it’s object mother, fixtures or the builder pattern, I can still keep my tests concise and understandable, and push down the setup logic into helper components.
The end result
I’m still doing top-down design, but now I’m supplying the real components as much as possible. I test at the detail as directed by the design of the component I’m building, but I allow the underlying components to do their work. This cuts down on mock setups that don’t actually match what can happen in production – if you use the real deal, you can’t fake an impossible situation.
There are downsides to this approach of which I’m well aware – defect isolation being a big one. But the tradeoff for an actual safety net instead of a noose makes up for this.
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