Test-driven development

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Test-Driven Development (TDD) is a software development technique consisting of short iterations where new test cases covering the desired improvement or new functionality are written first, then the production code necessary to pass the tests is implemented, and finally the software is refactored to accommodate changes. The availability of tests before actual development ensures rapid feedback after any change. Practitioners emphasize that test-driven development is a method of designing software, not merely a method of testing.

Test-Driven Development began to receive publicity in the early twenty-first century as an aspect of Extreme Programming, but more recently is creating more general interest in its own right[1].

Along with other techniques, the concept can also be applied to the improvement and removal of software defects from legacy code that was not developed in this way [2].

Contents

Test-driven development requires that an automated unit test, defining requirements of the code, is written before each aspect of the code itself. These tests contain assertions that are either true or false. Running the tests gives rapid confirmation of correct behaviour as the code evolves and is refactored. Testing frameworks based on the xUnit concept (see the list of unit testing frameworks for an exhaustive list) provide a mechanism for creating and running sets of automated test cases.

The following sequence is based on the book Test-Driven Development by Example [3], which many consider to be the original source text on the concept in its modern form.

In test-driven development, each new feature begins with writing a test. This test must inevitably fail because it is written before the feature has been implemented. In order to write a test, the developer must understand the specification and the requirements of the feature clearly. This may be accomplished through use cases and user stories to cover the requirements and exception conditions. This could also imply an invariant, or modification of an existing test. This is a differentiating feature of test-driven development versus writing unit tests after the code is written: it makes you focus on the requirements before writing the code, a subtle but important difference.

This validates that the test harness is working correctly and that the new test does not mistakenly pass without requiring any new code.

The new test should also fail for the expected reason. This step tests the test itself, in the negative. A "negative test" is something familiar to testers, to make sure a feature fails when it should fail (e.g. bad input data). It typically follows or is "paired" with one or more "positive tests" that make sure things work as expected (e.g. good input data). ("Make sure it works, then change one thing to make it break and make sure it breaks.") The entire suite of unit tests act to serve this need, cross-checking each other to make sure "negative tests" fail for the expected reasons.

This technique avoids the syndrome of writing tests that always pass, and therefore aren't worth much. Running the new test to see it fail the first time is a vital "sanity check".

The next step is to write some code that will cause the test to pass. The new code written at this stage will not be perfect and may, for example, pass the test in an inelegant way. That is acceptable because later steps will improve and hone it.

It is important that the code written is only designed to pass the test; no further (and therefore untested) functionality should be predicted and 'allowed for' at any stage.

If all test cases now pass, the programmer can be confident that the code meets all the tested requirements. This is a good point from which to begin the final step of the cycle.

Now the code can be cleaned up as necessary. By re-running the test cases, the developer can be confident that refactoring is not damaging any existing functionality. The concept of removing duplication is an important aspect of any software design. In this case, however, it also applies to removing any duplication between the test code and the production code — for example magic numbers or strings that were repeated in both, in order to make the test pass in step 3.

Starting with another new test, the cycle is then repeated to push forward the functionality. The size of the steps can be as small as the developer likes, or get larger if s/he feels more confident. If the code written to satisfy a test does not fairly quickly do so, then the step-size may have been too big, and maybe the smaller testable steps should be used instead. When using external libraries it is important not to make increments that are so small as to be effectively merely testing the library itself [1], unless there is some reason to believe that the library is buggy or is not sufficiently feature complete to serve all the needs of the main program being written.

There are various aspects to using test-driven development, for example the principles of "Keep It Simple, Stupid" (KISS) and "You Ain't Gonna Need It" (YAGNI). By focusing on writing only the code necessary to pass tests, designs can be cleaner and clearer than is often achieved by other methods[3]. (some people also suggest the principle "Fake it, till you make it")

To achieve some advanced design concept (such as a Design Pattern), tests are written that will generate that design. The code may remain simpler than the target pattern, but still pass all required tests. This can be unsettling at first but it allows the developer to focus only on what is important.

Test-driven development requires the programmer to first fail the test cases. The idea is to ensure that the test really works and can catch an error. Once this is shown, the normal cycle will commence. This has been coined the "Test-Driven Development Mantra", known as red/green/refactor where red means fail and green is pass.

Test-driven development constantly repeats the steps of adding test cases that fail, passing them, and refactoring. Receiving the expected test results at each stage reinforces the programmer's mental model of the code, boosts confidence and increases productivity.

Programmers using pure TDD on new ("greenfield") projects report they only rarely feel the need to invoke a debugger. Used in conjunction with a Version control system, when tests fail unexpectedly, reverting the code to the last version that passed all tests may often be more productive than debugging.[4][5]

Test-driven development can help to build software better and faster. It offers more than just simple validation of correctness, but can also drive the design of a program. By focusing on the test cases first, one must imagine how the functionality will be used by clients (in this case, the test cases). Therefore, the programmer is only concerned with the interface and not the implementation. This benefit is complementary to Design by Contract as it approaches code through test cases rather than through mathematical assertions or preconceptions.

The power test-driven development offers is the ability to take small steps when required. It allows a programmer to focus on the task at hand as the first goal is to make the test pass. Exceptional cases and error handling are not considered initially. Tests to create these extraneous circumstances are implemented separately. Another advantage is that test-driven development, when used properly, ensures that all written code is covered by a test. This can give the programmer, and subsequent users, a greater level of trust in the code.

While it is true that more code is required with TDD than without TDD because of the unit test code, total code implementation time is typically shorter.[6] Large numbers of tests help to limit the number of defects in the code. The early and frequent nature of the tests helps to catch defects early in the development cycle, preventing them from becoming endemic and expensive problems. Eliminating defects early in the process usually avoids lengthy and tedious debugging later in the project.

TDD can lead to more modularized, flexible, and extensible code. This effect often comes about because the methodology requires that the developer think of the software in terms of small units that can be written and tested independently and integrated together later. This leads to smaller, more focused classes, looser coupling, and cleaner interfaces. The use of the Mock Object design pattern also contributes to the overall modularization of the code because this pattern requires that the code be written so that modules can be switched easily between mock versions for unit testing or "real" version for deployment.

 This section does not cite any references or sources.
Please improve this section by adding citations to reliable sources. Unverifiable material may be challenged and removed. (October 2007)

Test-driven development, as a design technique, can produce inappropriate and low-quality code just as rapidly as high-quality code. A team should use other techniques, such as discussion and code reviews for example, to ensure not only that the correct features are implemented, but that the resulting code uses acceptable styles. Several Extreme Programming techniques, like Pair Programming and collective code ownership in general, help notice and correct such bad designs.

James Carr has created a catalog of TDD anti-patterns [1], as discussed on the TDD mailing list, and others have proposed that Tester Driven Development (note: TestER driven development, as distinct from Test-driven development) itself is a design anti-pattern.

Test-driven development only proves correctness of design and functionality according to the test cases written. An incorrect test that does not represent the specifications will produce incorrect code. Some of the emphasis on correctness and design shifts to designing test cases, because they are the drivers. As a result, a test-driven development is only as good as its tests. Due to the rapid alternation of tasks described above, of course each developer is responsible for their own tests—they should not be written in bulk, in advance, for example.

(Contrarily, code that submits to tests through all phases of its growth will achieve many Design For Test goals implicitly. When developers only write code that can indeed be tested, verification with formal unit tests becomes easier.)

As a design technique, test-driven development is unlikely to produce new algorithms, although it will verify their behaviour. Computer science research should therefore only use it in conjunction with other techniques. Automated testing may not be feasible at the limits of computer science (cryptography, robustness, artificial intelligence, computer security etc).[citation needed]

TDD is difficult to use in some situations, such as graphical user interfaces or relational databases, where systems with complex input and output were not designed for isolated unit testing or refactoring.

The use of the Mock Object design pattern is necessary in order to control the scope of dependencies involved in unit tests. However, when creating mock objects to interact with the module being tested, it is necessary that the developer have a good understanding of the behavior of the entities that are being mocked. Failure to achieve this understanding can lead to problems when the modules are deployed into a "real life" environment and they receive input they were not expecting or give output the environment can not handle. In many instances, creating mock objects that function realistically enough to allow for appropriate unit testing can be difficult and time consuming.

Test-suite code clearly has to be able to access the code it is testing. On the other hand normal design criteria such as information hiding, encapsulation and the separation of concerns should not be compromised. Therefore unit test code for TDD is usually written within the same project or module as the code being tested. In object oriented design this still does not provide access to private data and methods. In some languages these can be made internal to allow test-suite access, but this is still a distortion of the original intent. Where the facility is available in the language, it may be better to provide the test code with privileged access to private features via partial classes during development.

In all cases, thought must be given to the question of deployment. When the final library or executable is assembled or built, is it desirable to include in it all the test code that was used in its development? If it is written within the project or module, maybe as partial classes, then it is likely that it would be included by default. This will make the delivered run-time much larger than necessary, and may introduce security and other unexpected problems. It is unlikely that test code compiled into a delivered binary will ever be run; it is mainly useful to a developer with full access to the source code.

In some compiled languages, this can largely be solved by the use of compiler directives surrounding all test code to prevent deployment. For example, in C

#if DEBUG
...//test class
#endif

In scripting languages, keeping all test code in separate folders may help remind users not to deploy it, for example to live web servers, especially if the folders have, for example '_DO_NOT_DEPLOY' as part of their name.

If a code project is going to be developed by the creation of several hundred test cases, and the developers are expected to rerun these tests very frequently throughout the development, then it is necessary for these tests to run extremely quickly. For this reason unit tests, as used in TDD, should never cross process boundaries, i.e. they should never lead to any calls to code running in a different process to the one under test. Much more so, they should never pause and wait for any network access, across host boundaries.

This appears to lead to a problem when the code under development relies on a database or a web service or any other external process or service. This is not a problem, however, but an opportunity and a driving force to design more modular, more testable and more re-usable code. Two steps are necessary:

  1. Whenever external access is going to be needed in the final design, an interface should be defined that prescribes the access that will be available.
  2. The interface should be implemented in two ways, one of which really accesses the external process, and the other is a fake or mock object. Fake objects need do little more than add a message such as "Person object saved" to a trace-log or to the console, if that. Mock objects differ in that they themselves contain test assertions that can make the test fail, for example, if the person's name and other data are not valid. Fake and mock object methods that return data, ostensibly from a data store or user, can help the test process by always returning the same, realistic data that the tests can rely upon.

The disadvantage of this approach is that the actual database or other external-access code is never tested by the TDD process. This omission must be avoided: other tests are needed that instantiate the test-driven code with its 'real' implementations of the interfaces discussed above. Many developers find it useful to keep these tests quite separate from the TDD unit tests, and refer to them as integration tests. There will be fewer of them, and they need be run less often than the unit tests. They can nonetheless be implemented using the same testing framework, for example xUnit.

Integration tests that alter any persistent store or database should be careful always to leave them in a state ready for re-use, even if any test fails. This can be achieved using some combination of the following techniques where relevant and available to the developer:

  • the TearDown method integrated into many test frameworks
  • try...catch...finally exception handling structures where these are available
  • database transactions where a transaction atomically includes perhaps a write, a read and a matching delete operation..

Frameworks such as jMock exist to make the process of creating and using mock objects easier.

  1. ^ a b Newkirk, JW and Vorontsov, AA. Test-Driven Development in Microsoft .NET, Microsoft Press, 2004.
  2. ^ Feathers, M. Working Effectively with Legacy Code, Prentice Hall, 2004
  3. ^ a b Beck, K. Test-Driven Development by Example, Addison Wesley, 2003
  4. ^ Clark, Mike. Test-Driven Development with JUnit Workshop. Clarkware Consulting, Inc.. Retrieved on 2007-11-01. “In fact, test-driven development actually helps you meet your deadlines by eliminating debugging time, minimizing design speculation and re-work, and reducing the cost and fear of changing working code.”
  5. ^ Llopis, Noel (20 February 2005). Stepping Through the Looking Glass: Test-Driven Game Development (Part 1). Games from Within. Retrieved on 2007-11-01. “Comparing [TDD] to the non-test-driven development approach, you're replacing all the mental checking and debugger stepping with code that verifies that your program does exactly what you intended it to do.”
  6. ^ Muller, Matthias M.; Padberg, Frank. About the Return on Investment of Test-Driven Development (PDF) 6. Universitat Karlsruhe, Germany. Retrieved on 2007-11-01.

* Three Rules of TDD

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