I'm looking to better understand I should test functions that have many substeps or subfunctions.
Let's say I have the functions
// Modify the state of class somehow
public void DoSomething(){
DoSomethingA();
DoSomethingB();
DoSomethingC();
}
Every function here is public. Each subfunction has 2 paths. So to test every path for DoSomething() I'd have 2*2*2 = 8 tests. By writing 8 tests for DoSomething() I will have indirectly tested the subfunctions too.
So should I be testing like this, or instead write unit tests for each of the subfunctions and then only write 1 test case that measures the final state of the class after DoSomething() and ignore all the possible paths? A total of 2+2+2+1 = 7 tests. But is it bad then that the DoSomething() test case will depend on the other unit test cases to have complete coverage?
There appears to be a very prevalent religious belief that testing should be unit testing. While I do not intend to underestimate the usefulness of unit testing, I would like to point out that it is just one possible flavor of testing, and its extensive (or even exclusive) use is indicative of people (or environments) that are somewhat insecure about what they are doing.
In my experience knowledge of the inner workings of a system is useful as a hint for testing, but not as an instrument for testing. Therefore, black box testing is far more useful in most cases, though that's admittedly in part because I do not happen to be insecure about what I am doing. (And that is in turn because I use assertions extensively, so essentially all of my code is constantly testing itself.)
Without knowing the specifics of your case, I would say that in general, the fact that DoSomething() works by invoking DoSomethingA() and then DoSomethingB() and then DoSomethingC() is an implementation detail that your black-box test should best be unaware of. So, I would definitely not test that DoSomething() invokes DoSomethingA(), DoSomethingB(), and DoSomethingC(), I would only test to make sure that it returns the right results, and using the knowledge that it does in fact invoke those three functions as a hint I would implement precisely those 7 tests that you were planning to use.
On the other hand, it should be noted that if DoSomethingA() and DoSomethingB() and DoSomethingC() are also public functions, then you should also test them individually, too.
Definitely test every subfunction seperately (because they're public).
It would help you find the problem if one pops up.
If DoSomething only uses other functions, I wouldn't bother writing additional tests for it. If it has some other logic, I would test it, but assume all functions inside work properly (if they're in a different class, mock them).
The point is finding what the function does that is not covered in other tests and testing that.
Indirect testing should be avoided. You should write unit tests for each function explicitly. After that You should mock submethods and test your main function. For example :
You have a method which inserts a user to DB and method is like this :
void InsertUser(User user){
var exists = SomeExternal.UserExists(user);
if(exists)
throw new Exception("bla bla bla");
//Insert codes here
}
If you want to test InsertUser function, you should mock external/sub/nested methods and test behaviour of InsertUser function.
This example creates two tests: 1 - "When user exists then Should throw Exception" 2 - "When user does not exist then Should insert user"
Related
I am wondering if I should unit test functions that have no control flow. This functions take some input, call a sequence of 5/6 other functions, then return some output.
Testing them seems a waste of time, since I don't see what I would be testing exactly. The other functions called already have unit test for them.
The main drawback for me is that I don't know what the output should be a priori, I would need to call the same functions in the test scripit to see if the results coincide; and then what am I testing? That the test function and the actual function have the same lines in the same order?
Thanks for any insight
Note: Same as last question, if you think it's primarily opinion based reformulate as "According to the principles advocated in Art of Unit Testing, should i unit test functions with no control flow?"
Short answer: yes, of course you do!
Long answer: how a method does something is in the end "implementation" detail. In that sense: you should not care at all if a method is using a switch, some if/elses, a loop, or just calls other methods in sequence.
Instead, you should understand the contract that your method provides: which input it takes; and what comes out of it (depending on the inputs maybe).
That is what you focus on: creating a setup where your method can run; to then check if the method upholds that contract.
Example:
public void foo(Bar bar) {
FooBar fooBar = bar.wobbel();
fooBar.throttle();
fooBar.rattle(this.someField);
}
that code above doesn't contain any control flow statements. But still, there are various points in there where things could go wrong (for example NullPointerExceptions). Don't you think it would be better to catch those using unit tests?
Suppose I have several unit tests in a test class ([TestClass] in VSUnit in my case). I'm trying to test just one thing in each test (doesn't mean just one Assert though). Imagine there's one test (e.g. Test_MethodA() ) that tests a method used in other tests as well. I do not want to put an assert on this method in other tests that use it to avoid duplicity/maintainability issues so I have the assert in only this one test. Now when this test fails, all tests that depend on correct execution of that tested method fail as well. I want to be able to locate the problem faster so I want to be somehow pointed to Test_MethodA. It would e.g. help if I could make some of the tests in the test class execute in a particular order and when they fail I'd start looking for cause of the failure in the first failing test. Do you have any idea how to do this?
Edit: By suggesting that a solution would be to execute the tests in a particular order I have probably went too far and in the wrong direction. I don't care about the order of the tests. It's just that some of the tests will always fail if a prequisite isn't valid. E.g. I have a test class that tests a DAO class (ok, probably not a UNIT test, but there's logic in the database stored procedures that needs to be tested but that's not the point here I think). I need to insert some records into a table in order to test that a method responsible for retrieving the records (let's call it GetAll()) gets them all in the correct order e.g. I do the insert by using a method on the DAO class. Let's call it Insert(). I have tests in place that verify that the Insert() method works as expected. Now I want to test the GetAll() method. In order to get the database in a desired state I use the Insert() method. If Insert() doesn't work, most tests for GetAll() will fail. I'd prefer to mark the tests that can't pass because Insert() doesn't work as inconclusive rather than failed. It would ease finding the cause of the problem if I know which method/test to look into first.
You can't (and shouldn't) execute unit tests in a specific order. The underlying reason for this is to prevent Interacting Tests - I realize that your motivation for requesting such a feature is different, but that's the reason why unit test frameworks don't allow you to order tests. In fact, last time I checked, xUnit.net even randomizes the order.
One could argue that the fact that some of your tests depend on a different method call on the same class is a symptom of tight coupling, but that's not always the case (state machines come to mind).
However, if possible, consider using a Back Door instead of the other method in question.
If you can't do either that or decouple the interdependency (e.g. by making the first method virtual and using the Extract and Override technique), you will have to live with it.
Here's an example:
public class MyClass
{
public virtual void FirstMethod() { // do something... }
public void SecondMethod() {}
}
Since FirstMethod is virtual, you can derive from MyClass and override its behavior. You can also use a dynamic mock to do that for you. With Moq, it would look like this:
var sutStub = new Mock<MyClass>();
// by default, Moq overrides all virtual methods without calling base
// Now invoke both methods in sequence:
sutStub.Object.FirstMethod(); // overriden by Moq, so it does nothing
sutSutb.Object.SecondMethod();
I think I would indeed have the assertion on the method_A() result in every tests relying on its result, even if this introduces some duplication. Then I would use the assertion message to point to the method_A() failure.
assert("method_A() returned true", true, rc);
Perhaps will I end extracting the method_A() call and the assertion into an helper function to remove the duplication.
Now let's imagine method_A() queries an object and returns it, or NULL when no object is found. Then this assertion is a guard ; and it is necessary with languages suchas C, C++ that do not have NullPointerException.
I'm afraid you can't do this. The only solution is to redesign your code and break it up into smaller methods so that unit tests can call these one by one. Of course this isn't always desirable.
With Visual Studio you can order your tests: see here. But I'd like to advise you to stay away from this technique as much as possible: unit tests are meant to be run anywhere, anytime and in every order.
EDIT: why is this a problem for you? All failing tests point to the same method anyway...
If a function just calls another function or performs actions. How do I test it? Currently, I enforce all the functions should return a value so that I could assert the function return values. However, I think this approach mass up the API because in the production code. I don't need those functions to return value. Any good solutions?
I think mock object might be a possible solution. I want to know when should I use assert and when should I use mock objects? Is there any general guide line?
Thank you
Let's use BufferedStream.Flush() as an example method that doesn't return anything; how would we test this method if we had written it ourselves?
There is always some observable effect, otherwise the method would not exist. So the answer can be to test for the effect:
[Test]
public void FlushWritesToUnderlyingStream()
{
var memory = new byte[10];
var memoryStream = new MemoryStream(memory);
var buffered = new BufferedStream(memoryStream);
buffered.Write(0xFF);
Assert.AreEqual(0x00, memory[0]); // not yet flushed, memory unchanged
buffered.Flush();
Assert.AreEqual(0xFF, memory[0]); // now it has changed
}
The trick is to structure your code so that these effects aren't too hard to observe in a test:
explicitly pass collaborator objects,
just like how the memoryStream is passed
to the BufferedStream in the constructor.
This is called dependency
injection.
program against an interface, just
like how BufferedStream is programmed
against the Stream interface. This enables
you to pass simpler, test-friendly implementations (like MemoryStream in this case) or use a mocking framework (like MoQ or RhinoMocks), which is all great for unit testing.
Sorry for not answering straight but ... are you sure you have the exact balance in your testing?
I wonder if you are not testing too much ?
Do you really need to test a function that merely delegates to another?
Returns only for the tests
I agree with you when you write you don't want to add return values that are useful only for the tests, not for production. This clutters your API, making it less clear, which is a huge cost in the end.
Also, your return value could seem correct to the test, but nothing says that the implementation is returning the return value that corresponds to the implementation, so the test is probably not proving anything anyway...
Costs
Note that testing has an initial cost, the cost of writing the test.
If the implementation is very easy, the risk of failure is ridiculously low, but the time spend testing still accumulates (over hundred or thousands cases, it ends up being pretty serious).
But more than that, each time you refactor your production code, you will probably have to refactor your tests also. So the maintenance cost of your tests will be high.
Testing the implementation
Testing what a method does (what other methods it calls, etc) is critized, just like testing a private method... There are several points made:
this is fragile and costly : any code refactoring will break the tests, so this increases the maintenance cost
Testing a private method does not bring much safety to your production code, because your production code is not making that call. It's like verifying something you won't actually need.
When a code delegates effectively to another, the implementation is so simple that the risk of mistakes is very low, and the code almost never changes, so what works once (when you write it) will never break...
Yes, mock is generally the way to go, if you want to test that a certain function is called and that certain parameters are passed in.
Here's how to do it in Typemock (C#):
Isolate.Verify.WasCalledWithAnyArguments(()=> myInstance.WeatherService("","", null,0));
Isolate.Verify.WasCalledWithExactArguments(()=> myInstance. StockQuote("","", null,0));
In general, you should use Assert as much as possible, until when you can't have it ( For example, when you have to test whether you call an external Web service API properly, in this case you can't/ don't want to communicate with the web service directly). In this case you use mock to verify that a certain web service method is correctly called with correct parameters.
"I want to know when should I use assert and when should I use mock objects? Is there any general guide line?"
There's an absolute, fixed and important rule.
Your tests must contain assert. The presence of assert is what you use to see if the test passed or failed. A test is a method that calls the "component under test" (a function, an object, whatever) in a specific fixture, and makes specific assertions about the component's behavior.
A test asserts something about the component being tested. Every test must have an assert, or it isn't a test. If it doesn't have assert, it's not clear what you're doing.
A mock is a replacement for a component to simplify the test configuration. It is a "mock" or "imitation" or "false" component that replaces a real component. You use mocks to replace something and simplify your testing.
Let's say you're going to test function a. And function a calls function b.
The tests for function a must have an assert (or it's not a test).
The tests for a may need a mock for function b. To isolate the two functions, you test a with a mock for function b.
The tests for function b must have an assert (or it's not a test).
The tests for b may not need anything mocked. Or, perhaps b makes an OS API call. This may need to be mocked. Or perhaps b writes to a file. This may need to be mocked.
Suppose you have a method:
public void Save(Entity data)
{
this.repositoryIocInstance.EntitySave(data);
}
Would you write a unit test at all?
public void TestSave()
{
// arrange
Mock<EntityRepository> repo = new Mock<EntityRepository>();
repo.Setup(m => m.EntitySave(It.IsAny<Entity>());
// act
MyClass c = new MyClass(repo.Object);
c.Save(new Entity());
// assert
repo.Verify(m => EntitySave(It.IsAny<Entity>()), Times.Once());
}
Because later on if you do change method's implementation to do more "complex" stuff like:
public void Save(Entity data)
{
if (this.repositoryIocInstance.Exists(data))
{
this.repositoryIocInstance.Update(data);
}
else
{
this.repositoryIocInstance.Create(data);
}
}
...your unit test would fail but it probably wouldn't break your application...
Question
Should I even bother creating unit tests on methods that don't have any return types* or **don't change anything outside of internal mock?
Don't forget that unit tests isn't just about testing code. It's about allowing you to determine when behaviour changes.
So you may have something that's trivial. However, your implementation changes and you may have a side effect. You want your regression test suite to tell you.
e.g. Often people say you shouldn't test setters/getters since they're trivial. I disagree, not because they're complicated methods, but someone may inadvertently change them through ignorance, fat-finger scenarios etc.
Given all that I've just said, I would definitely implement tests for the above (via mocking, and/or perhaps it's worth designing your classes with testability in mind and having them report status etc.)
It's true your test is depending on your implementation, which is something you should avoid (though it is not really that simple sometimes...) and is not necessarily bad. But these kind of tests are expected to break even if your change doesn't break the code.
You could have many approaches to this:
Create a test that really goes to the database and check if the state was changed as expected (it won't be a unit test anymore)
Create a test object that fakes a database and do operations in-memory (another implementation for your repositoryIocInstance), and verify the state was changed as expected. Changes to the repository interface would incurr in changes to this object as well. But your interfaces shouldn't be changing much, right?
See all of this as too expensive, and use your approach, which may incur on unnecessarily breaking tests later (but once the chance is low, it is ok to take the risk)
Ask yourself two questions. "What is the manual equivalent of this unit test?" and "is it worth automating?". In your case it would be something like:
What is manual equivalent?
- start debugger
- step into "Save" method
- step into next, make sure you're inside IRepository.EntitySave implementation
Is it worth automating? My answer is "no". It is 100% obvious from the code.
From hundreds of similar waste tests I didn't see a single which would turn out to be useful.
The general rule of thumb is, that you test all things, that could probably break. If you are sure, that the method is simple enough (and stays simple enough) to not be a problem, that let it out with testing.
The second thing is, you should test the contract of the method, not the implementation. If the test fails after a change, but not the application, then your test tests not the right thing. The test should cover cases that are important for your application. This should ensure, that every change to the method that doesn't break the application also don't fail the test.
A method that does not return any result still changes the state of your application. Your unit test, in this case, should be testing whether the new state is as intended.
"your unit test would fail but it probably wouldn't break your application"
This is -- actually -- really important to know. It may seem annoying and trivial, but when someone else starts maintaining your code, they may have made a really bad change to Save and (improbably) broken the application.
The trick is to prioritize.
Test the important stuff first. When things are slow, add tests for trivial stuff.
When there isn't an assertion in a method, you are essentially asserting that exceptions aren't thrown.
I'm also struggling with the question of how to test public void myMethod(). I guess if you do decide to add a return value for testability, the return value should represent all salient facts necessary to see what changed about the state of the application.
public void myMethod()
becomes
public ComplexObject myMethod() {
DoLotsOfSideEffects()
return new ComplexObject { rows changed, primary key, value of each column, etc };
}
and not
public bool myMethod()
DoLotsOfSideEffects()
return true;
The short answer to your question is: Yes, you should definitely test methods like that.
I assume that it is important that the Save method actually saves the data. If you don't write a unit test for this, then how do you know?
Someone else may come along and remove that line of code that invokes the EntitySave method, and none of the unit tests will fail. Later on, you are wondering why items are never persisted...
In your method, you could say that anyone deleting that line would only be doing so if they have malign intentions, but the thing is: Simple things don't necessarily stay simple, and you better write the unit tests before things get complicated.
It is not an implementation detail that the Save method invokes EntitySave on the Repository - it is part of the expected behavior, and a pretty crucial part, if I may say so. You want to make sure that data is actually being saved.
Just because a method does not return a value doesn't mean that it isn't worth testing. In general, if you observe good Command/Query Separation (CQS), any void method should be expected to change the state of something.
Sometimes that something is the class itself, but other times, it may be the state of something else. In this case, it changes the state of the Repository, and that is what you should be testing.
This is called testing Inderect Outputs, instead of the more normal Direct Outputs (return values).
The trick is to write unit tests so that they don't break too often. When using Mocks, it is easy to accidentally write Overspecified Tests, which is why most Dynamic Mocks (like Moq) defaults to Stub mode, where it doesn't really matter how many times you invoke a given method.
All this, and much more, is explained in the excellent xUnit Test Patterns.
I have a basic understanding of mock and fake objects, but I'm not sure I have a feeling about when/where to use mocking - especially as it would apply to this scenario here.
Mock objects are useful when you want to test interactions between a class under test and a particular interface.
For example, we want to test that method sendInvitations(MailServer mailServer) calls MailServer.createMessage() exactly once, and also calls MailServer.sendMessage(m) exactly once, and no other methods are called on the MailServer interface. This is when we can use mock objects.
With mock objects, instead of passing a real MailServerImpl, or a test TestMailServer, we can pass a mock implementation of the MailServer interface. Before we pass a mock MailServer, we "train" it, so that it knows what method calls to expect and what return values to return. At the end, the mock object asserts, that all expected methods were called as expected.
This sounds good in theory, but there are also some downsides.
Mock shortcomings
If you have a mock framework in place, you are tempted to use mock object every time you need to pass an interface to the class under the test. This way you end up testing interactions even when it is not necessary. Unfortunately, unwanted (accidental) testing of interactions is bad, because then you're testing that a particular requirement is implemented in a particular way, instead of that the implementation produced the required result.
Here's an example in pseudocode. Let's suppose we've created a MySorter class and we want to test it:
// the correct way of testing
testSort() {
testList = [1, 7, 3, 8, 2]
MySorter.sort(testList)
assert testList equals [1, 2, 3, 7, 8]
}
// incorrect, testing implementation
testSort() {
testList = [1, 7, 3, 8, 2]
MySorter.sort(testList)
assert that compare(1, 2) was called once
assert that compare(1, 3) was not called
assert that compare(2, 3) was called once
....
}
(In this example we assume that it's not a particular sorting algorithm, such as quick sort, that we want to test; in that case, the latter test would actually be valid.)
In such an extreme example it's obvious why the latter example is wrong. When we change the implementation of MySorter, the first test does a great job of making sure we still sort correctly, which is the whole point of tests - they allow us to change the code safely. On the other hand, the latter test always breaks and it is actively harmful; it hinders refactoring.
Mocks as stubs
Mock frameworks often allow also less strict usage, where we don't have to specify exactly how many times methods should be called and what parameters are expected; they allow creating mock objects that are used as stubs.
Let's suppose we have a method sendInvitations(PdfFormatter pdfFormatter, MailServer mailServer) that we want to test. The PdfFormatter object can be used to create the invitation. Here's the test:
testInvitations() {
// train as stub
pdfFormatter = create mock of PdfFormatter
let pdfFormatter.getCanvasWidth() returns 100
let pdfFormatter.getCanvasHeight() returns 300
let pdfFormatter.addText(x, y, text) returns true
let pdfFormatter.drawLine(line) does nothing
// train as mock
mailServer = create mock of MailServer
expect mailServer.sendMail() called exactly once
// do the test
sendInvitations(pdfFormatter, mailServer)
assert that all pdfFormatter expectations are met
assert that all mailServer expectations are met
}
In this example, we don't really care about the PdfFormatter object so we just train it to quietly accept any call and return some sensible canned return values for all methods that sendInvitation() happens to call at this point. How did we come up with exactly this list of methods to train? We simply ran the test and kept adding the methods until the test passed. Notice, that we trained the stub to respond to a method without having a clue why it needs to call it, we simply added everything that the test complained about. We are happy, the test passes.
But what happens later, when we change sendInvitations(), or some other class that sendInvitations() uses, to create more fancy pdfs? Our test suddenly fails because now more methods of PdfFormatter are called and we didn't train our stub to expect them. And usually it's not only one test that fails in situations like this, it's any test that happens to use, directly or indirectly, the sendInvitations() method. We have to fix all those tests by adding more trainings. Also notice, that we can't remove methods no longer needed, because we don't know which of them are not needed. Again, it hinders refactoring.
Also, the readability of test suffered terribly, there's lots of code there that we didn't write because of we wanted to, but because we had to; it's not us who want that code there. Tests that use mock objects look very complex and are often difficult to read. The tests should help the reader understand, how the class under the test should be used, thus they should be simple and straightforward. If they are not readable, nobody is going to maintain them; in fact, it's easier to delete them than to maintain them.
How to fix that? Easily:
Try using real classes instead of mocks whenever possible. Use the real PdfFormatterImpl. If it's not possible, change the real classes to make it possible. Not being able to use a class in tests usually points to some problems with the class. Fixing the problems is a win-win situation - you fixed the class and you have a simpler test. On the other hand, not fixing it and using mocks is a no-win situation - you didn't fix the real class and you have more complex, less readable tests that hinder further refactorings.
Try creating a simple test implementation of the interface instead of mocking it in each test, and use this test class in all your tests. Create TestPdfFormatter that does nothing. That way you can change it once for all tests and your tests are not cluttered with lengthy setups where you train your stubs.
All in all, mock objects have their use, but when not used carefully, they often encourage bad practices, testing implementation details, hinder refactoring and produce difficult to read and difficult to maintain tests.
For some more details on shortcomings of mocks see also Mock Objects: Shortcomings and Use Cases.
A unit test should test a single codepath through a single method. When the execution of a method passes outside of that method, into another object, and back again, you have a dependency.
When you test that code path with the actual dependency, you are not unit testing; you are integration testing. While that's good and necessary, it isn't unit testing.
If your dependency is buggy, your test may be affected in such a way to return a false positive. For instance, you may pass the dependency an unexpected null, and the dependency may not throw on null as it is documented to do. Your test does not encounter a null argument exception as it should have, and the test passes.
Also, you may find its hard, if not impossible, to reliably get the dependent object to return exactly what you want during a test. That also includes throwing expected exceptions within tests.
A mock replaces that dependency. You set expectations on calls to the dependent object, set the exact return values it should give you to perform the test you want, and/or what exceptions to throw so that you can test your exception handling code. In this way you can test the unit in question easily.
TL;DR: Mock every dependency your unit test touches.
Rule of thumb:
If the function you are testing needs a complicated object as a parameter, and it would be a pain to simply instantiate this object (if, for example it tries to establish a TCP connection), use a mock.
You should mock an object when you have a dependency in a unit of code you are trying to test that needs to be "just so".
For example, when you are trying to test some logic in your unit of code but you need to get something from another object and what is returned from this dependency might affect what you are trying to test - mock that object.
A great podcast on the topic can be found here