Useful design patterns for unit testing/TDD?

Reading this question has helped me solidify some of the problems I've always had with unit-testing, TDD, et al.

Since coming across the TDD approach to development I knew that it was the right path to follow. Reading various tutorials helped me understand how to make a start, but they have always been very simplistic - not really something that one can apply to an active project. The best I've managed is writing tests around small parts of my code - things like libraries, that are used by the main app but aren't integrated in any way. While this has been useful it equates to about 5% of the code-base. There's very little out there on how to go to the next step, to help me get some tests into the main app.

Comments such as "Most code without unit tests is built with hard dependencies (i.e.'s new's all over the place) or static methods." and "...it's not rare to have a high level of coupling between classes, hard-to-configure objects inside your class [...] and so on." have made me realise that the next step is understanding how to de-couple code to make it testable.

What should I be looking at to help me do this? Is there a specific set of design patterns that I need to understand and start to implement which will allow easier testing?

Here Mike Clifton describes 24 test patterns from 2004. Its a useful heuristic when designing unit tests.

http://www.codeproject.com/Articles/5772/Advanced-Unit-Test-Part-V-Unit-Test-Patterns

Pass/Fail Patterns

These patterns are your first line of defence (or attack, depending on your perspective) to guarantee good code. But be warned, they are deceptive in what they tell you about the code.

• The Simple-Test Pattern
• The Code-Path Pattern
• The Parameter-Range Pattern

Data Transaction Patterns

Data transaction patterns are a start at embracing the issues of data persistence and communication. More on this topic is discussed under "Simulation Patterns". Also, these patterns intentionally omit stress testing, for example, loading on the server. This will be discussed under "Stress-Test Patterns".

• The Simple-Data-I/O Pattern
• The Constraint-Data Pattern
• The Rollback Pattern

Collection Management Patterns

A lot of what applications do is manage collections of information. While there are a variety of collections available to the programmer, it is important to verify (and thus document) that the code is using the correct collection. This affects ordering and constraints.

• The Collection-Order Pattern
• The Enumeration Pattern The
• Collection-Constraint Pattern
• The Collection-Indexing Pattern

Performance Patterns

Unit testing should not just be concerned with function but also with form. How efficiently does the code under test perform its function? How fast? How much memory does it use? Does it trade off data insertion for data retrieval effectively? Does it free up resources correctly? These are all things that are under the purview of unit testing. By including performance patterns in the unit test, the implementer has a goal to reach, which results in better code, a better application, and a happier customer.

• The Performance-Test Pattern

Process Patterns

Unit testing is intended to test, well, units...the basic functions of the application. It can be argued that testing processes should be relegated to the acceptance test procedures, however I don't buy into this argument. A process is just a different type of unit. Testing processes with a unit tester provide the same advantages as other unit testing--it documents the way the process is intended to work and the unit tester can aid the implementer by also testing the process out of sequence, rapidly identifying potential user interface issues as well. The term "process" also includes state transitions and business rules, both of which must be validated.

• The Process-Sequence Pattern
• The Process-State Pattern
• The Process-Rule Pattern

Simulation Patterns

Data transactions are difficult to test because they often require a preset configuration, an open connection, and/or an online device (to name a few). Mock objects can come to the rescue by simulating the database, web service, user event, connection, and/or hardware with which the code is transacting. Mock objects also have the ability to create failure conditions that are very difficult to reproduce in the real world--a lossy connection, a slow server, a failed network hub, etc.

• Mock-Object Pattern
• The Service-Simulation Pattern
• The Bit-Error-Simulation Pattern
• The Component-Simulation Pattern

Multithreading Patterns

Unit testing multithreaded applications is probably one of the most difficult things to do because you have to set up a condition that by its very nature is intended to be asynchronous and therefore non-deterministic. This topic is probably a major article in itself, so I will provide only a very generic pattern here. Furthermore, to perform many threading tests correctly, the unit tester application must itself execute tests as separate threads so that the unit tester isn't disabled when one thread ends up in a wait state

• The Signalled Pattern
• The Deadlock-Resolution Pattern

Stress-Test Patterns

Most applications are tested in ideal environments--the programmer is using a fast machine with little network traffic, using small datasets. The real world is very different. Before something completely breaks, the application may suffer degradation and respond poorly or with errors to the user. Unit tests that verify the code's performance under stress should be met with equal fervor (if not more) than unit tests in an ideal environment.

• The Bulk-Data-Stress-Test Pattern
• The Resource-Stress-Test Pattern
• The Loading-Test Pattern

Presentation Layer Patterns

One of the most challenging aspects of unit testing is verifying that information is getting to the user right at the presentation layer itself and that the internal workings of the application are correctly setting presentation layer state. Often, presentation layers are entangled with business objects, data objects, and control logic. If you're planning on unit testing the presentation layer, you have to realize that a clean separation of concerns is mandatory. Part of the solution involves developing an appropriate Model-View-Controller (MVC) architecture. The MVC architecture provides a means to develop good design practices when working with the presentation layer. However, it is easily abused. A certain amount of discipline is required to ensure that you are, in fact, implementing the MVC architecture correctly, rather than just in word alone.

• The View-State Test Pattern
• The Model-State Test Pattern

I'd say you need mainly two things to test, and they go hand in hand:

• Interfaces, interfaces, interfaces
• dependency injection; this in conjunction with interfaces will help you swap parts at will to isolate the modules you want to test. You want to test your cron-like system that sends notifications to other services? instanciate it and substitute your real-code implementation for everything else by components obeying the correct interface but hard-wired to react in the way you want to test: mail notification? test what happens when the smtp server is down by throwing an exception

I myself haven't mastered the art of unit testing (and i'm far from it), but this is where my main efforts are going currently. The problem is that i still don't design for tests, and as a result my code has to bend backwards to accomodate...

Michael Feather's book Working Effectively With Legacy Code is exactly what you're looking for. He defines legacy code as 'code without tests' and talks about how to get it under test.

As with most things it's one step at a time. When you make a change or a fix try to increase the test coverage. As time goes by you'll have a more complete set of tests. It talks about techniques for reducing coupling and how to fit test pieces between application logic.

As noted in other answers dependency injection is one good way to write testable (and loosely coupled in general) code.

Arrange, Act, Assert is a good example of a pattern that helps you structure your testing code around particular use cases.

Here's some hypothetical C# code that demonstrates the pattern.

[TestFixture]
public class TestSomeUseCases() {

    // Service we want to test
    private TestableServiceImplementation service;

    // IoC-injected mock of service that's needed for TestableServiceImplementation
    private Mock<ISomeService> dependencyMock;

    public void Arrange() {
        // Create a mock of auxiliary service
        dependencyMock = new Mock<ISomeService>();
        dependencyMock.Setup(s => s.GetFirstNumber(It.IsAny<int>)).Return(1);

        // Create a tested service and inject the mock instance
        service = new TestableServiceImplementation(dependencyMock.Object);
    }

    public void Act() {
        service.ProcessFirstNumber();
    }

    [SetUp]
    public void Setup() {
        Arrange();
        Act();
    }

    [Test]
    public void Assert_That_First_Number_Was_Processed() {
        dependencyMock.Verify(d => d.GetFirstNumber(It.IsAny<int>()), Times.Exactly(1));
    }
}

If you have a lot of scenarios to test, you can extract a common abstract class with concrete Arrange & Act bits (or just Arrange) and implement the remaining abstract bits & test functions in the inherited classes that group test functions.

Gerard Meszaros' xUnit Test Patterns: Refactoring Test Code is chock full of patterns for unit testing. I know you're looking for patterns on TDD, but I think you will find a lot of useful material in this book

The book is on safari so you can get a really good look at what's inside to see if it might be helpful: http://my.safaribooksonline.com/9780131495050

> have made me realise that the next step is understanding how to de-couple code to make it testable. > > What should I be looking at to help me do this? Is there a specific set of design patterns that I need to understand and start to implement which will allow easier testing?

Right on! SOLID is what you are looking for (yes, really). I keep recommending these 2 ebooks, specially the one on SOLID for the issue at hand.

You also have to understand that its very hard if you are introducing unit testing to an existing code base. Unfortunately tightly coupled code is far too common. This doesn't mean not to do it, but for a good time it'll be just like you mentioned, tests will be more concentrated in small pieces.

Over time these grow into a larger scope, but it does depend on the size of the existing code base, the size of the team and how many are actually doing it instead of adding to the problem.

Design patterns aren't directly relevant to TDD, as they are implementation details. You shouldn't try to fit patterns into your code just because they exist, but rather they tend to appear as your code evolves. They also become useful if your code is smelly, since they help resolve such issues. Don't develop code with design patterns in mind, just write code. Then get tests passing, and refactor.

A lot of problems like this can be solved with proper encapsulation. Or, you might have this problem if you are mixing your concerns. Say you've got code that validates a user, validates a domain object, then saves the domain object all in one method or class. You've mixed your concerns, and you aren't going to be happy. You need to separate those concerns (authentication/authorization, business logic, persistence) so you can test them in isolation.

Design patterns help, but a lot of the exotic ones have very narrow problems to which they can be applied. Patterns like composite, command, are used often, and are simple.

The guideline is: if it is very difficult to test something, you can probably refactor it into smaller problems and test the refactored bits in isolation. So if you have a 200 line method with 5 levels of if statements and a few for-loops, you might want to break that sucker up.

So, start by seeing if you can make complicated code simpler by separating your concerns, and then see if you can make complicated code simpler by breaking it up. Of course if a design pattern jumps out at you, then go for it.

Dependency Injection/IoC. Also read up on dependency injection frameworks such as SpringFramework and google-guice. They also target how to write testable code.