The key difference, to me, is that integration tests reveal if a feature is working or is broken, since they stress the code in a scenario close to reality. They invoke one or more software methods or features and test if they act as expected.
On the opposite, a Unit test testing a single method relies on the (often wrong) assumption that the rest of the software is correctly working, because it explicitly mocks every dependency.
Hence, when a unit test for a method implementing some feature is green, it does not mean the feature is working.
Say you have a method somewhere like this:
public SomeResults DoSomething(someInput) {
var someResult = [Do your job with someInput];
Log.TrackTheFactYouDidYourJob();
return someResults;
}
DoSomething
is very important to your customer: it's a feature, the only thing that matters. That's why you usually write a Cucumber specification asserting it: you wish to verify and communicate the feature is working or not.
Feature: To be able to do something
In order to do something
As someone
I want the system to do this thing
Scenario: A sample one
Given this situation
When I do something
Then what I get is what I was expecting for
No doubt: if the test passes, you can assert you are delivering a working feature. This is what you can call Business Value.
If you want to write a unit test for DoSomething
you should pretend (using some mocks) that the rest of the classes and methods are working (that is: that, all dependencies the method is using are correctly working) and assert your method is working.
In practice, you do something like:
public SomeResults DoSomething(someInput) {
var someResult = [Do your job with someInput];
FakeAlwaysWorkingLog.TrackTheFactYouDidYourJob(); // Using a mock Log
return someResults;
}
You can do this with Dependency Injection, or some Factory Method or any Mock Framework or just extending the class under test.
Suppose there's a bug in Log.DoSomething()
.
Fortunately, the Gherkin spec will find it and your end-to-end tests will fail.
The feature won't work, because Log
is broken, not because [Do your job with someInput]
is not doing its job. And, by the way, [Do your job with someInput]
is the sole responsibility for that method.
Also, suppose Log
is used in 100 other features, in 100 other methods of 100 other classes.
Yep, 100 features will fail. But, fortunately, 100 end-to-end tests are failing as well and revealing the problem. And, yes: they are telling the truth.
It's very useful information: I know I have a broken product. It's also very confusing information: it tells me nothing about where the problem is. It communicates me the symptom, not the root cause.
Yet, DoSomething
's unit test is green, because it's using a fake Log
, built to never break. And, yes: it's clearly lying. It's communicating a broken feature is working. How can it be useful?
(If DoSomething()
's unit test fails, be sure: [Do your job with someInput]
has some bugs.)
Suppose this is a system with a broken class:
A single bug will break several features, and several integration tests will fail.
On the other hand, the same bug will break just one unit test.
Now, compare the two scenarios.
The same bug will break just one unit test.
- All your features using the broken
Log
are red
- All your unit tests are green, only the unit test for
Log
is red
Actually, unit tests for all modules using a broken feature are green because, by using mocks, they removed dependencies. In other words, they run in an ideal, completely fictional world. And this is the only way to isolate bugs and seek them. Unit testing means mocking. If you aren't mocking, you aren't unit testing.
The difference
Integration tests tell what's not working. But they are of no use in guessing where the problem could be.
Unit tests are the sole tests that tell you where exactly the bug is. To draw this information, they must run the method in a mocked environment, where all other dependencies are supposed to correctly work.
That's why I think that your sentence "Or is it just a unit test that spans 2 classes" is somehow displaced. A unit test should never span 2 classes.
This reply is basically a summary of what I wrote here: Unit tests lie, that's why I love them.
Look, there's no easy way to do this. I'm working on a project that is inherently multithreaded. Events come in from the operating system and I have to process them concurrently.
The simplest way to deal with testing complex, multithreaded application code is this: If it's too complex to test, you're doing it wrong. If you have a single instance that has multiple threads acting upon it, and you can't test situations where these threads step all over each other, then your design needs to be redone. It's both as simple and as complex as this.
There are many ways to program for multithreading that avoids threads running through instances at the same time. The simplest is to make all your objects immutable. Of course, that's not usually possible. So you have to identify those places in your design where threads interact with the same instance and reduce the number of those places. By doing this, you isolate a few classes where multithreading actually occurs, reducing the overall complexity of testing your system.
But you have to realize that even by doing this, you still can't test every situation where two threads step on each other. To do that, you'd have to run two threads concurrently in the same test, then control exactly what lines they are executing at any given moment. The best you can do is simulate this situation. But this might require you to code specifically for testing, and that's at best a half step towards a true solution.
Probably the best way to test code for threading issues is through static analysis of the code. If your threaded code doesn't follow a finite set of thread safe patterns, then you might have a problem. I believe Code Analysis in VS does contain some knowledge of threading, but probably not much.
Look, as things stand currently (and probably will stand for a good time to come), the best way to test multithreaded apps is to reduce the complexity of threaded code as much as possible. Minimize areas where threads interact, test as best as possible, and use code analysis to identify danger areas.
Best Answer
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