I would like to start doing more unit testing in my applications, but it seems to me that most of the stuff I do is just no suitable to be unit tested. I know how unit tests are supposed to work in textbook examples, but in real world applications they do not seem of much use.
Some applications I write have very simple logic and complex interactions with things that are outside my control. For instance I would like to write a daemon which reacts to signals sent by some applications, and changes some user settings in the OS. I can see three difficulties:
first I have to be able to talk with the applications and be notified of their events;
then I need to interact with OS whenever I receive a signal, in order to change the appropriate user settings;
finally all of this should work as a daemon.
All these things are potentially delicate: I will have to browse possibly complex APIs and I may introduce bugs, say by misinterpreting some parameters. What can unit testing do for me? I can mock both the external application and the OS, and check that given a signal from the application, I will call the appropriate API method on the OS. This is... well, the trivial part of the application.
Actually most of the things I do involve interaction with databases, the filesystem or other applications, and these are the most delicate parts.
For another example look at my build tool PHPmake. I would like to refactor it, as it is not very well-written, but I fear to do this as I have no tests. So I would like to add some. The point is that the things which may be broken by refactoring may not be caught by unit tests:
One of things to do is deciding which things are to be built and which one are already up to date, and this depends on the time of last modification of the files. This time is actually changed by external processes, when some build command is fired.
I want to be sure that the output of external processes is displayed correctly. Sometimes the buikd commands require some input, and that should be also managed correctly. But I do not know a priori which processes will be ran - it may be anything.
Some logic is involved in pattern matching, and this may seem to be testable part. But the functions which do the pattern matching use (ni addition to their own logic) the PHP function glob, which works with the filesystem. If I just mock a tree in place of the actual filesystem, glob will not work.
I could go on with more examples, but the point is the following. Unless I have some delicate algorithms, most of what I do involves interaction with external resources, and this is not suitable for unit testing. More that this, often this interaction is actually the non-trivial part. Still many people see unit testing as a basic tool. What am I missing? How can I learn be a better tester?
I think you open a number of issues in your question.
Firstly, when your application integrates with external environments such as OS, other threads, etc. then you have to separate (1) the logic that is tied in with the external enviroment and (2) your business-code.. that is, the stuff your application does. This is no different to how you would separate GUI and SERVER in an application (or web application).
Secondly, you ask if you should test simple logic. I'd say, it depends. Often simple fetch/store functionality is nice to have tests for. It's like the foundation of your application.. hence its important. Other business stuff built upon your foundation that is very simple, you may easily find yourself both feeling that you are wasting your time, and mostly you are :-)
Thirdly, refactory an existing program and testing it in its existing state may be a problem. If your PHP program produces a set of files on the basis of some input, well, maybe thats your entry point to tests are. Sure the tests may be high-level, but it's an easy way to ensure that after the refactoring, your program produces the same output. Hence, aim for higher-level tests in that situation in the start phase of your refactoring efforts.
I'd like to recommend some literature, but I can only come up with one title. "Working Effectively with Legacy Code" By Micheal Feathers. It's a good start. Another would be "xUnit Test Patterns: Refactoring Test Code" by Gerard Meszaros (although that book is much more sloppy and FULL of copy paste text).
As regards your issue about existing code bases that aren't currently covered by tests in which you would like to start refactoring, I would suggest reading:
Working Effectively with Legacy Code By Micheal Feathers.
That book gives you techniques on how to deal with the issues you might be facing with PHPMake. It provides ways to introduce seams for testing, where there previously weren't any.
Additionally, with code that touches say the file systems, you can abstract the file system calls behind a thin wrapper, using the Adapter Pattern. The unit tests would be against a fake implementation of the abstract interface that the wrapping class implements.
At some point you get to a low enough level where a unit of code can't be isolated for unit testing as these depend on library or API calls (such as in the production implementation of the wrapper). Once this happens integration tests are really the only automated developer tests you can write.
I recommend this google tech-talk on unit testing.
The video boils down to
write your code so that it knows as little about how it will be used as possible. The less assumptions your code makes, the easier it is to test. Avoid complex logic in constructors, the use of singletons, static class members, and so on.
isolate your code from the external world (comms, databases, real time), and make sure that your code only talks to your isolation layer. Otherwise, writing tests will be a nightmare in terms of 'fake environment' setup.
unit tests should test stories; that is what we really understand and care for; given a class with a method foo(), testFoo() is uninformative. They actually recommend test names like itShouldCloseConnectionEvenWhenExceptionThrown(). Ideally, your stories should cover enough functionality that you can rebuild the spec from the stories.
NOTE: the video and this post use Java as an example; however, the main points stand for any language.
"Unit tests" tests one unit of your code. No external tools should be involved. This seems to be complicated for your first app (without knowing to much about it ;)) but the phpMake is unit-testable - I'm sure ... because ant, gradle and maven are unit-testable too ;)!
But of course you can test your first application automated too. There are several different layers one could test an application.
So the task for you is to find an automated way to test your app - be it integration testing or whatever.
E.g. you could write shell scripts, which asserts some output! With that you make sure your application behaves correctly ...
Tests of interactions with external resources are integration tests, not unit tests.
Tests of your code to see how it would behave if particular external interactions had occurred can be unit tests. These should be done by writing your code to use dependency injection, and then, in the unit test, injecting mock objects as dependencies.
For example, consider a piece of code that adds the results of a call to one service to the results of a call to another service:
public int AddResults(IService1 svc1, IService2 svc2, int parameter)
{
return svc1.Call(parameter) + svc2.Call(parameter);
}
You can test this by passing in mock objects for the two services:
private class Service1Returns1 : IService1
{
public int Call(int parameter){return 1;}
}
private class Service2Returns1 : IService2
{
public int Call(int parameter){return 1;}
}
public void Test1And1()
{
Assert.AreEqual(2, AddResults(new Service1Returns1(), new Service2Returns1(), 0));
}
First of all, if unit testing doesn't seem like it would be much use in your applications, why do you even want to start doing more of it? What is motivating you to care about it? It is definitely a waste of time if a) you do everything perfect the first time and nothing ever changes or b) you decide it's a waste of time and do it poorly.
If you do think that you really want to do unit testing, the answer to your questions are all the same: encapsulation. In your daemon example, you could create a ApplcationEventObeservationProxy with a very narrow interface that just implements pass through methods. The purpose of this class is to do nothing but completely encapsulate the rest of your code from the third-party event observing library (nothing means nothing -- no logic here). Do the same thing for OS settings. Then you can completely unit test the class that does actions based on events. I'd recommend have a separate class for the daemon-ness that just wraps your main class -- it will make the testing easier.
There are a couple of benefits to this approach outside of unit testing. One is that if you encapsulate the code that interacts directly with the OS, it's easier to switch it out. This kind of code is particularly prone to breakage outside of your control (i.e., MS patchsets). You will also probably want to support more than one OS, and if the OS specific logic is not tangled with the rest of your logic, it will be easier. The other benefit is that you'll be forced to realize that there is more business logic in your app than you think. :)
Finally, don't forget that unit testing is a foundation for a good product, but not the only ingredient. Having a set of tests that explore and verify the OS API calls you'll be using is a good strategy for the "hard" parts of this problem. You should also have end to end tests that ensure the events in your applications cause the OS setting changes.
As other answers suggested Working Effectively with Legacy Code By Micheal Feathers is a good read. If you have to deal with legacy code, and you want to make sure that the systems interaction work as expected, try writing integration tests first. And then it is more appropriate to write Unit Tests to test the behaviour of methods that are valued from the requirements point of view. You Tests serve a whole different purpose than the integration tests. Unit Tests are more likely to improve the design of your system than testing how everything hangs to gather.
Related
I have a more general question:
Assuming I have a web application, for example using the Struts2 Framework.
Therefore it becomes quite complicated to write Unit tests for functions, as you have to mock every aspect of the Framework.
The Database+Connection, The Session, a LDAP-Connection or what ever else is needed, which I do not have written on my own
It would be much easier to write the unit Tests so, that they run in a WebInterface inside the Base-Application, as all these things then already would exist.
The question:
Would you guys still consider this as unit testing?
Some thoughts..
The question is very general. My suggestion is that you still want to write some sort of Unit Tests for number of reasons. Firstly you can run them as an automated test suite so if something breaks you know quickly. Secondly you get a better designed system - Your objects are loosely coupled. You get more confident on the code you write.
If you have a framework harder to test,
a. Try abstracting away some dependencies, so they code can be injected without interfering with real instances.
b. Use a testing framework that can break any tightly coupled harder dependencies.
Harder to provide a comprehensive answer, but this is the general direction, which I would suggest.
You should consider what you really want to test first. A framework, for its definition, will use the classes you provide to do some "magic". Do you want to test that has already been tested "magic" or the business core of the app you programmed?.
Also, something you should consider, is where to stop testing. You probably don't want to test the connection to the database (considering what you wrote) so just mock it.
Take in consideration that you will have to test just one functionality at the time, don't think of having, for example, the database connection and the ldap in the same test, it wouldn't be unit testing.
Take a look at this tutorial also :http://tutorials.jenkov.com/java-unit-testing/index.html
The tests at my new job are nothing like the tests I have encountered before.
When they're writing their unit tests (presumably before the code), they create a class starting with "When". The name describes the scenario under which the tests will run (the fixture). They'll created subclasses for each branch through the code. All of the tests within the class start with "should" and they test different aspects of the code after running. So, they will have a method for verifying that each mock (DOC) is called correctly and for checking the return value, if applicable. I am a little confused by this method because it means the exact same execution code is being run for each test and this seems wasteful. I was wondering if there is a technique similar to this that they may have adapted. A link explaining the style and how it is supposed to be implemented would be great. I sounds similar to some approaches of BDD I've seen.
I also noticed that they've moved the repeated calls to "execute" the SUT into the setup methods. This causes issues when they are expecting exceptions, because they can't use built-in tools for performing the check (Python unittest's assertRaises). This also means storing the return value as a backing field of the test class. They also have to store many of the mocks as backing fields. Across class hierarchies it becomes difficult to tell the configuration of each mock.
They also test code a little differently. It really comes down to what they consider an integration test. They mock out anything that steals the context away from the function being tested. This can mean private methods within the same class. I have always limited mocking to resources that can affect the results of the test, such as databases, the file system or dates. I can see some value in this approach. However, the way it is being used now, I can see it leading to fragile tests (tests that break with every code change). I get concerned because without an integration test, in this case, you could be using a 3rd party API incorrectly but your unit tests would still pass. I'd like to learn more about this approach as well.
So, any resources about where to learn more about some of these approaches would be nice. I'd hate to pass up a great learning opportunity just because I don't understand they way they are doing things. I would also like to stop focusing on the negatives of these approaches and see where the benefits come in.
If I understood you explanation in the first paragraph correctly, that's quite similar to what I often do. (Depending on whether the testing framework makes it easy or not. Also many mocking frameworks don't support it, but spy frameworks like Mockito do better.)
For example see the stack example here which has a common setup (adding things to the stack) and then a bunch of independent tests which each check one thing. Here's still another example, this time one where none of the tests (#Test) modify the common fixture (#Before), but each of them focuses on checking just one independent thing that should happen. If the tests are very well focused, then it should be possible to change the production code to make any single test fail while all other tests pass (I wrote about that recently in Unit Test Focus Isolation).
The main idea is to have each test check a single feature/behavior, so that when tests fail it's easier to find out why it failed. See this TDD tutorial for more examples and to learn that style.
I'm not worried about the same code paths executed multiple times, when it takes a millisecond to run one test (if it takes more than a couple of seconds to run all unit tests, the tests are probably too big). From your explanation I'm more worried that the tests might be too tightly coupled to the implementation, instead of the feature, if it's systematic that there is one test for each mock. The name of the test would be a good indicator of how well structured or how fragile the tests are - does it describe a feature or how that feature is implemented.
About mocking, a good book to read is Growing Object-Oriented Software Guided by Tests. One should not mock 3rd party APIs (APIs which you don't own and can't modify), for the reason you already mentioned, but one should create an abstraction over it which better fits the needs of the system using it and works the way you want it. That abstraction needs to be integration tested with the 3rd party API, but in all tests using the abstraction you can mock it.
First, the pattern that you are using is based on Cucumber - here's a link. The style is from the BDD (Behavior-driven development) approach. It has two advantages over traditional TDD:
Language - one of the tenants of BDD is that the language you use influences the thoughts you have by forcing you to speak in the language of the end user, you will end up writing different tests than when you write tests from the focus of a programmer
Tests lock code - BDD locks the code at the appropriate level. One problem common in testing is that you write a large number of tests, which makes your codebase more brittle as when you change the code you must also change a large number of tests too. BDD forces you to lock the behavior of your code, rather than the implementation of your code. This way, when a test breaks, it is more likely to be meaningful.
It is worth noting that you do not have to use the Cucumber style of testing to achieve these affects and using it does add an extra layer of overhead. But very few programmers have been successful in keeping the BDD mindset while using traditional xUnit tools (TDD).
It also sounds like you have some scenarios where you would like to say 'When I do , then verify '. Because the current BDD xUnit frameworks only allow you to verify primitives (strings, ints, doubles, booleans....), this usually results in a large number of individual tests (one for each Assert). It is possible to do more complicated verifications using a Golden Master paradigm test tool, such as ApprovalTests. Here's a video example of this.
Finally, here's a link to Dan North's blog - he started it all.
I've been working on an ASP.NET MVC project for about 8 months now. For the most part I've been using TDD, some aspects were covered by unit tests only after I had written the actual code. In total the project pretty has good test coverage.
I'm quite pleased with the results so far. Refactoring really is much easier and my tests have helped me uncover quite a few bugs even before I ran my software the first time. Also, I have developed more sophisticated fakes and helpers to help me minimize the testing code.
However, what I don't really like is the fact that I frequently find myself having to update existing unit tests to account for refactorings I made to the software. Refactoring the software is now quick and painless, but refactoring my unit tests is quite boring and tedious. In fact the cost of maintaining my unit tests is higher than the cost of writing them in the first place.
I am wondering whether I might be doing something wrong or if this relation of cost of test development vs. test maintenance is normal. I've already tried to write as many tests as possible so that these cover my user stories instead of systematically covering my object's interface as suggested in this blog article.
Also, do you have any further tips on how to write TDD tests so that refactoring breaks as few tests as possible?
Edit: As Henning and tvanfosson correctly remarked, it's usually the setup part that is most expensive to write and maintain. Broken tests are (in my experience) usually a result of a refactoring to the domain model that is not compatible with the setup part of those tests.
This is a well-known problem that can be addressed by writing tests according to best practices. These practices are described in the excellent xUnit Test Patterns. This book describes test smells that lead to unmaintanable tests, as well as provide guidance on how to write maintanable unit tests.
After having followed those patterns for a long time, I wrote AutoFixture which is an open source library that encapsulates a lot of those core patterns.
It works as a Test Data Builder, but can also be wired up to work as an Auto-Mocking container and do many other strange and wonderful things.
It helps a lot with regards to maintainance because it raises the abstraction level of writing a test considerably. Tests become a lot more declarative because you can state that you want an instance of a certain type instead of explicitly writing how it is created.
Imagine that you have a a class with this constructor signature
public MyClass(Foo foo, Bar bar, Sgryt sgryt)
As long as AutoFixture can resolve all the constructor arguments, you can simply create a new instance like this:
var sut = fixture.CreateAnonymous<MyClass>();
The major benefit is that if you decide to refactor the MyClass constructor, no tests break because AutoFixture will figure it out for you.
That's just a glimpse of what AutoFixture can do. It's a stand-alone library, so it will work with your unit testing framework of choice.
You might be writing your unit tests too close to your classes. What you should do is to test public APIs. When I mean public APIs, I don't mean public methods on all your classes, I mean your public controllers.
By having your tests mimicking how a user would interact with your controller part without ever touching your model classes or helper function directly, you allow yourself to refactor your code without having to refactor your tests. Of course, sometimes even your public API changes and then you'll still have to change your tests, but that will happen way less often.
The downside of this approach is that you'll often have to go through complex controller setup just to test a new tiny helper function you want to introduce, but I think that in the end, it's worth it. Moreover, you'll end up organizing your test code in a smarter way, making that setup code easier to write.
This article helped me a lot: http://msdn.microsoft.com/en-us/magazine/cc163665.aspx
On the other hand, there's no miracle method to avoid refactoring unit tests.
Everything comes with a price, and that's especially true if you want to do unit testing.
What I think he means is that it is the setup part that is quite tedious to maintain.
We're having the exact same problem, especially when we introduce new dependecies, split dependecies, or otherwise change how the code is supposed to be used.
For the most part, when I write and maintain unit tests, I spend my time in writing the setup/arrange code.
In many of our tests we have the exact same setup code, and we've sometimes used private helper methods to do the actual setup, but with different values.
However, that isn't a really good thing, because we still have to create all those values in every test. So, we are now looking into writing our tests in a more specification/BDD style, which should help to reduce the setup code, and therefore the amount of time spent in maintaining the tests.
A few resources you can check out is http://elegantcode.com/2009/12/22/specifications/, and BDD style of testing with MSpec http://elegantcode.com/2009/07/05/mspec-take-2/
Most of the time I see such refactorings affecting the set up of the unit test, frequently involving adding dependencies or changing expectations on these dependencies. These dependencies may be introduced by later features but affect earlier tests. In these cases I've found it to be very useful to refactor the set up code so that it is shared by multiple tests (parameterized so that it can be flexibly configured). Then when I need to make a change for a new feature that affects the set up, I only need to refactor the tests in a single place.
Two area's that I focus on when I start to feel the refactor pain around setup are making my unit tests more specific and my method/class's smaller. Essentially I find I am getting away from SOLID / SRP. Or I have tests that are trying to do to much.
It is worth noting that I do try and stay away from BDD/context spec the further from the UI I get. Testing a behavior is great, but always leads me (perhaps I am not doing it right?) to bigger messier tests, with more context specification than I like.
Another way I have seen this to happen to me is as code debit, creeping into methods that grow their business logic over time. Of course there are always big methods and class with multiple dependencies, but the less I have the less 'test rewrite' I have.
If you find yourself creating complicated test scaffolding involving deep object graphs like Russian dolls, consider refactoring your code so that the Class Under Test gets exactly what it needs in its constructor/arguments, rather than having it walk the graph.
intead of:
public class A {
public void foo(B b) {
String someField = b.getC().getD().getSomeField();
// ...
}
}
Change it to:
public class A {
public void foo(String someField) {
// ...
}
}
Then your test setup becomes trivial.
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We have tried to introduce unit testing to our current project but it doesn't seem to be working. The extra code seems to have become a maintenance headache as when our internal Framework changes we have to go around and fix any unit tests that hang off it.
We have an abstract base class for unit testing our controllers that acts as a template calling into the child classes' abstract method implementations i.e. Framework calls Initialize so our controller classes all have their own Initialize method.
I used to be an advocate of unit testing but it doesn't seem to be working on our current project.
Can anyone help identify the problem and how we can make unit tests work for us rather than against us?
Tips:
Avoid writing procedural code
Tests can be a bear to maintain if they're written against procedural-style code that relies heavily on global state or lies deep in the body of an ugly method.
If you're writing code in an OO language, use OO constructs effectively to reduce this.
Avoid global state if at all possible.
Avoid statics as they tend to ripple through your codebase and eventually cause things to be static that shouldn't be. They also bloat your test context (see below).
Exploit polymorphism effectively to prevent excessive ifs and flags
Find what changes, encapsulate it and separate it from what stays the same.
There are choke points in code that change a lot more frequently than other pieces. Do this in your codebase and your tests will become more healthy.
Good encapsulation leads to good, loosely coupled designs.
Refactor and modularize.
Keep tests small and focused.
The larger the context surrounding a test, the more difficult it will be to maintain.
Do whatever you can to shrink tests and the surrounding context in which they are executed.
Use composed method refactoring to test smaller chunks of code.
Are you using a newer testing framework like TestNG or JUnit4?
They allow you to remove duplication in tests by providing you with more fine-grained hooks into the test lifecycle.
Investigate using test doubles (mocks, fakes, stubs) to reduce the size of the test context.
Investigate the Test Data Builder pattern.
Remove duplication from tests, but make sure they retain focus.
You probably won't be able to remove all duplication, but still try to remove it where it's causing pain. Make sure you don't remove so much duplication that someone can't come in and tell what the test does at a glance. (See Paul Wheaton's "Evil Unit Tests" article for an alternative explanation of the same concept.)
No one will want to fix a test if they can't figure out what it's doing.
Follow the Arrange, Act, Assert Pattern.
Use only one assertion per test.
Test at the right level to what you're trying to verify.
Think about the complexity involved in a record-and-playback Selenium test and what could change under you versus testing a single method.
Isolate dependencies from one another.
Use dependency injection/inversion of control.
Use test doubles to initialize an object for testing, and make sure you're testing single units of code in isolation.
Make sure you're writing relevant tests
"Spring the Trap" by introducing a bug on purpose and make sure it gets caught by a test.
See also: Integration Tests Are A Scam
Know when to use State Based vs Interaction Based Testing
True unit tests need true isolation. Unit tests don't hit a database or open sockets. Stop at mocking these interactions. Verify you talk to your collaborators correctly, not that the proper result from this method call was "42".
Demonstrate Test-Driving Code
It's up for debate whether or not a given team will take to test-driving all code, or writing "tests first" for every line of code. But should they write at least some tests first? Absolutely. There are scenarios in which test-first is undoubtedly the best way to approach a problem.
Try this exercise: TDD as if you meant it (Another Description)
See also: Test Driven Development and the Scientific Method
Resources:
Test Driven by Lasse Koskela
Growing OO Software, Guided by Tests by Steve Freeman and Nat Pryce
Working Effectively with Legacy Code by Michael Feathers
Specification By Example by Gojko Adzic
Blogs to check out: Jay Fields, Andy Glover, Nat Pryce
As mentioned in other answers already:
XUnit Patterns
Test Smells
Google Testing Blog
"OO Design for Testability" by Miskov Hevery
"Evil Unit Tests" by Paul Wheaton
"Integration Tests Are A Scam" by J.B. Rainsberger
"The Economics of Software Design" by J.B. Rainsberger
"Test Driven Development and the Scientific Method" by Rick Mugridge
"TDD as if you Meant it" exercise originally by Keith Braithwaite, also workshopped by Gojko Adzic
Are you testing small enough units of code? You shouldn't see too many changes unless you are fundamentally changing everything in your core code.
Once things are stable, you will appreciate the unit tests more, but even now your tests are highlighting the extent to which changes to your framework are propogated through.
It is worth it, stick with it as best you can.
Without more information it's hard to make a decent stab at why you're suffering these problems. Sometimes it's inevitable that changing interfaces etc. will break a lot of things, other times it's down to design problems.
It's a good idea to try and categorise the failures you're seeing. What sort of problems are you having? E.g. is it test maintenance (as in making them compile after refactoring!) due to API changes, or is it down to the behaviour of the API changing? If you can see a pattern, then you can try to change the design of the production code, or better insulate the tests from changing.
If changing a handful of things causes untold devastation to your test suite in many places, there are a few things you can do (most of these are just common unit testing tips):
Develop small units of code and test
small units of code. Extract
interfaces or base classes where it
makes sense so that units of code
have 'seams' in them. The more
dependencies you have to pull in (or
worse, instantiate inside the class
using 'new'), the more exposed to
change your code will be. If each
unit of code has a handful of
dependencies (sometimes a couple or
none at all) then it is better
insulated from change.
Only ever assert on what the test
needs. Don't assert on intermediate,
incidental or unrelated state. Design by
contract and test by contract (e.g.
if you're testing a stack pop method,
don't test the count property after
pushing -- that should be in a
separate test).
I see this problem
quite a bit, especially if each test
is a variant. If any of that
incidental state changes, it breaks
everything that asserts on it
(whether the asserts are needed or
not).
Just as with normal code, use factories and builders
in your unit tests. I learned that one when about 40 tests
needed a constructor call updated after an API change...
Just as importantly, use the front
door first. Your tests should always
use normal state if it's available. Only used interaction based testing when you have to (i.e. no state to verify against).
Anyway the gist of this is that I'd try to find out why/where the tests are breaking and go from there. Do your best to insulate yourself from change.
One of the benefits of unit testing is that when you make changes like this you can prove that you're not breaking your code. You do have to keep your tests in sync with your framework, but this rather mundane work is a lot easier than trying to figure out what broke when you refactored.
I would insists you to stick with the TDD. Try to check your Unit Testing framework do one RCA (Root Cause Analysis) with your team and identify the area.
Fix the unit testing code at suite level and do not change your code frequently specially the function names or other modules.
Would appreciate if you can share your case study well, then we can dig out more at the problem area?
Good question!
Designing good unit tests is hard as designing the software itself. This is rarely acknowledged by developers, so the result is often hastily-written unit tests that require maintenance whenever the system under test changes. So, part of the solution to your problem could be spending more time to improve the design of your unit tests.
I can recommend one great book that deserves its billing as The Design Patterns of Unit-Testing
HTH
If the problem is that your tests are getting out of date with the actual code, you could do one or both of:
Train all developers to not pass code reviews that don't update unit tests.
Set up an automatic test box that runs the full set of units tests after every check-in and emails those who break the build. (We used to think that that was just for the "big boys" but we used an open source package on a dedicated box.)
Well if the logic has changed in the code, and you have written tests for those pieces of code, I would assume the tests would need to be changed to check the new logic. Unit tests are supposed to be fairly simple code that tests the logic of your code.
Your unit tests are doing what they are supposed to do. Bring to the surface any breaks in behavior due to changes in the framework, immediate code or other external sources. What this is supposed to do is help you determine if the behavior did change and the unit tests need to be modified accordingly, or if a bug was introduced thus causing the unit test to fail and needs to be corrected.
Don't give up, while its frustrating now, the benefit will be realized.
I'm not sure about the specific issues that make it difficult to maintain tests for your code, but I can share some of my own experiences when I had similar issues with my tests breaking. I ultimately learned that the lack of testability was largely due to some design issues with the class under test:
Using concrete classes instead of interfaces
Using singletons
Calling lots of static methods for business logic and data access instead of interface methods
Because of this, I found that usually my tests were breaking - not because of a change in the class under test - but due to changes in other classes that the class under test was calling. In general, refactoring classes to ask for their data dependencies and testing with mock objects (EasyMock et al for Java) makes the testing much more focused and maintainable. I've really enjoyed some sites in particular on this topic:
Google testing blog
The guide to writing testable code
Why should you have to change your unit tests every time you make changes to your framework? Shouldn't this be the other way around?
If you're using TDD, then you should first decide that your tests are testing the wrong behavior, and that they should instead verify that the desired behavior exists. Now that you've fixed your tests, your tests fail, and you have to go squish the bugs in your framework until your tests pass again.
Everything comes with price of course. At this early stage of development it's normal that a lot of unit tests have to be changed.
You might want to review some bits of your code to do more encapsulation, create less dependencies etc.
When you near production date, you'll be happy you have those tests, trust me :)
Aren't your unit tests too black-box oriented ? I mean ... let me take an example : suppose you are unit testing some sort of container, do you use the get() method of the container to verify a new item was actually stored, or do you manage to get an handle to the actual storage to retrieve the item directly where it is stored ? The later makes brittle tests : when you change the implementation, you're breaking the tests.
You should test against the interfaces, not the internal implementation.
And when you change the framework you'd better off trying to change the tests first, and then the framework.
I would suggest investing into a test automation tool. If you are using continuous integration you can make it work in tandem. There are tools aout there which will scan your codebase and will generate tests for you. Then will run them. Downside of this approach is that its too generic. Because in many cases unit test's purpose is to break the system.
I have written numerous tests and yes I have to change them if the codebase changes.
There is a fine line with automation tool you would definatelly have better code coverage.
However, with a well wrttien develper based tests you will test system integrity as well.
Hope this helps.
If your code is really hard to test and the test code breaks or requires much effort to keep in sync, then you have a bigger problem.
Consider using the extract-method refactoring to yank out small blocks of code that do one thing and only one thing; without dependencies and write your tests to those small methods.
The extra code seems to have become a maintenance headache as when our internal Framework changes we have to go around and fix any unit tests that hang off it.
The alternative is that when your Framework changes, you don't test the changes. Or you don't test the Framework at all. Is that what you want?
You may try refactoring your Framework so that it is composed from smaller pieces that can be tested independently. Then when your Framework changes, you hope that either (a) fewer pieces change or (b) the changes are mostly in the ways in which the pieces are composed. Either way will get you better reuse of both code and tests. But real intellectual effort is involved; don't expect it to be easy.
I found that unless you use IoC / DI methodology that encourages writing very small classes, and follow Single Responsibility Principle religiously, the unit-tests end up testing interaction of multiple classes which makes them very complex and therefore fragile.
My point is, many of the novel software development techniques only work when used together. Particularly MVC, ORM, IoC, unit-testing and Mocking. The DDD (in the modern primitive sense) and TDD/BDD are more independent so you may use them or not.
Sometime designing the TDD tests launch questioning on the design of the application itself. Check if your classes have been well designed, your methods are only performing one thing a the time ... With good design it should be simple to write code to test simple method and classes.
I have been thinking about this topic myself. I'm very sold on the value of unit tests, but not on strict TDD. It seems to me that, up to a certain point, you may be doing exploratory programming where the way you have things divided up into classes/interfaces is going to need to change. If you've invested a lot of time in unit tests for the old class structure, that's increased inertia against refactoring, painful to discard that additional code, etc.
I have finally got in my mind what worried me about Dependency Injection and similar techniques that should make unit tests easier. Let's take this example:
public interface IRepository { void Item Find(); a lot of other methods here; }
[Test]
public void Test()
{
var repository = Mock<IRepository>();
repository.Expect(x => x.Find());
var service = new Service(repository);
service.ProcessWithItem();
}
Now, what's wrong with the code above? It's that our test roughly peeks into ProcessWithItem() implementation. What if it wants to do "from x in GetAll() where x..." - but no, our test knows what is going to happen there. And that's just a simple example. Imaging few calls that our test now is tied with, and when we want to change from GetAll() to a better GetAllFastWithoutStuff() inside the method... our test(s) are broken. Please change them. A lot of crappy work that happens so often without any real need.
And that's what often makes me to stop write tests. I just don't see how I can test without knowing implementation details. And knowing them, tests are now very fragile and pain to do.
Sure, it's not about interface (or DI) only. POCOs (and POJOs, why not) also suffer from the same thing, but they're now tied with the data, not with the interface. But the principle is the same - our final assertion is tightly coupled with our knowledge of what our SUT is going to do. "Yes you HAVE to provide this field, sir, and this better be of this value".
As a consequence, tests ARE going to fail - soon and often. This is pain. And the problem.
Are there any techniques to deal with this? AutoMockingContainer (which basically takes care all ALL methods and nested DI hierarchies) looks promising, but with its own drawback. Anything else?
Dependency Injection, per se, would let you inject an implementation of IRepository that accepts whatever calls are made on it, checks that the invariants and preconditions are satisfied, and returns results satisfying the postconditions. When you choose to inject a mock object that has very specific expectations for what methods will be called, then yes, you're doing highly implementation-specific testing -- but Dependency Injection is totally innocent in the matter, since it never dictates WHAT you should inject; rather, your beef appears to be with Mocking -- in fact, specifically the somewhat-automated mocking approach that you have chosen to use, which is one based on very specific expectations.
Mocking with very specific expectations IS indeed useful for white-box testing only. Depending on the tools / frameworks / libraries you're using (and you're not even specifying the exact programming language in a tag, so I assume your question is totally open ended) you may be able to specify the degrees of freedom allowed (these calls are allowed to come in any orders, these arguments must only satisfy the following preconditions, etc, etc). However, I don't know of an automated tool to perform exactly what you need for opaque-box testing, which is the "generic, tolerant implementation of yonder interface with all the ''programming by contract'' checks that are needed and no other".
What I tend to do over the life of a project is to build up a library of "not quite mocks" for the major interfaces needed. In some cases those may be somewhat obvious from the start, but in other cases they emerge incrementally as I'm considering some major refactoring, as follows (typical scenario)...:
The early stages of the refactoring break some aspect of the fragile strong-expectations mocking that I have cheaply put in place initially, I ponder whether to just tweak the expectations or go whole hog, if I decide it's not a one-off (i.e. the return in future refactorings and tests will justify the investment) then I hand-code a good "not quite mock" and stash it away in the project's specific bag of tricks -- actually often reusable across projects; such classes/packages as MockFilesystem, MockBigtable, MockDom, MockHttpClient, MockHttpServer, etc etc, go into a project-agnostic repository and get reused for testing all kinds of future projects (and in fact may be shared with other teams across the company, if several teams are using filesystem interfaces, bigtable interfaces, DOMs, http client/server interfaces, etc etc, that are uniform across the teams).
I acknowledge that the use of the word "mock" may be slightly inappropriate here if you take "mock" to refer specifically to the precise-expectation style of "fake implementation for testing purposes" of interfaces. Maybe Stub, Shim, Fake, Test, or some other prefix yet might be preferable (I do tend to use Mock for historical reasons, except when I remember to specifically call it Fake or the like;-).
If I was using languages with clear and precise way to express in the language itself the various design-by-contract specs in an interface, I imagine I'd get automatic tool support for most of this faking/shimming/etc; however I mostly code in other languages so I have to do a bit more manual work here. But I think that's a separate issue.
I read the excellent book http://www.manning.com/rainsberger/.
I would like to provide some insight I gained from it.
I believe several advice could help you to reduce the coupling between your tests and your implementation.
Edited: included in this coupling is the test asserting that the code under test calls some methods. Calling some method is never a functional need, it is an implementation concern. It relates to an interface other than the one being tested.
In many cases, the testing should be about the external behavior of an interface, and be completely black-box testing them.
The author gives the example that the test classes should be in a different package than the class to test. At first, I was sure this was wrong, because it makes it more difficult to test protected and package methods. But he argues that you should only test the external behavior of a system, that is the public methods. The non-public methods are implementation-details, and testing it results in coupling the test with the implementation. This was very insightful to me.
By the way, this book has so many excellent practical advice on how to design tests (say JUnit tests), that I would buy it on my own money if it wasn't provided by the company! ;-)
An excellent other advice from the book was to test at the functionality level, not the method level. For example, testing the add() method for a list requires trusted size() and get() methods, but they in turn require add() so we have a loop, we can't test safely. But testing the list's behavior globally (accross all methods) when adding involves testing the three methods at the same time, not proving that each is correct in isolation, but checking that together they provide the expected behavior. Often, when you try to test one of your methods in isolation, you cannot write a sensible test without using other methods, so you end up testing the implementation instead ; the consequence are coupling between test and implementation.
Only test functionalities, not methods.
Also, note that testing using external ressources (the database being the more common, but many others exist) is much slower, requires some access (IP, licence etc) from the executing machine, require a started container, may be sensitive to simultaneous access (a database can't run reliably multiple JUnit campaign at the same time), and has many other drawbacks. If all your tests use external resources, then you are in trouble, you can't run all your tests all the time, from any machine, from many machines at once, etc. So I understood (still from the book):
Test only once each external resource (database for example), in a dedicated test that is not a unit-test, but an integration test (although it can still use the same JUnit technology if appropriate).
Test enough dedicated tests to trust the resource is working. Then, other tests should never test it again, this is a waste, they should trust it.
Note that the current Maven best-practices give similar advice (see free book "Better builds with Maven"). I believe this is not a coincidence:
The JUnits in the test directory of a project are real unit tests. They run every time you do something with your project (except just compile).
The integration and functional tests should be provided in a different project, an integration-test project. They only run in a much later (optional) phase, after you have deployed your whole application in the container.
As a consequence, tests ARE going to
fail - soon and often. This is pain.
And the problem.
Well yes, unit tests can depend on internal implementation details. And sure, such "white box" tests are more brittle than "black box" tests which only rely on the externally published contract.
But I don't agree that this has to cause regular test failures. Think about how you arrived at testing with mocks in the first place: you've used dependency injection to limit the responsibilities of the class, to decrease coupling to other code, and to enable testing the class in isolation.
Are there any techniques to deal with
this?
A good unit test can only fail if you change the class under test, even if it depends on internal implementation details. And you can limit the responsibilities and coupling (to other classes) of your class, so that you will rarely have to change it.
In practice you'll have to be pragmatic; every now and then you'll write "unit tests" that are actually integration tests involving multiple classes or over-sized classes. Brittle tests depending on internal implementation details are more dangerous in that case. But for truly TDD-style classes, not so much.
Remember when you're writing a test you're not testing your repository, you're testing your Service class. In this specific example ProcessWithItem method. You create your expectations for repository object. By the way, you forgot to specify expected return for your x.Find method. That's the beauty of DI that you isolate everything from the code you about to write (I assume you do TDD).
To be honest I cannot relate to the problem you describe.
Yeah, that's one of the big problems with unit testing. That, and refactoring. And design changes that are a regular occurrence with Agile. And the inexperience of those creating the tests. And etc etc...
I think the only thing the average non-critical-systems developer can do is pick and choose your battles wisely. Early in development identify the truly critical paths and test those. Weigh the likelihood of that code changing before spending lots of time testing the rest of it.
If anybody figures it all out please let us know.