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Test-Driven JavaScript Development: Tools of the Trade

This chapter takes a look at essential and useful tools to support a test-driven workflow. After an overview of available testing frameworks, you will learn to set up and run JsTestDriver. In addition to a testing framework, this chapter looks at tools such as coverage reports and continuous integration.
This chapter is from the book

This chapter is from the book

In Chapter 1, Automated Testing, we developed a very simple testCase function, capable of running basic unit tests with test case setup and teardown methods. Although rolling our own test framework is a great exercise, there are many frameworks already available for JavaScript and this chapter explores a few of them.

In this chapter we will take a look at "the tools of the trade"—essential and useful tools to support a test-driven workflow. The most important tool is of course the testing framework, and after an overview of available frameworks, we will spend some time setting up and running JsTestDriver, the testing framework used for most of this book's example code. In addition to a testing framework, this chapter looks at tools such as coverage reports and continuous integration.

3.1 xUnit Test Frameworks

In Chapter 1, Automated Testing, we coined xUnit as the term used to describe testing frameworks that lean on the design of Java's JUnit and Smalltalk's SUnit, originally designed by Kent Beck. The xUnit family of test frameworks is still the most prevalent way of writing automated tests for code, even though the past few years have seen a rise in usage for so-called behavior-driven development (or BDD) testing frameworks.

3.1.1 Behavior-Driven Development

Behavior-driven development, or BDD, is closely related to TDD. As discussed in Chapter 2, The Test-Driven Development Process, TDD is not about testing, but rather about design and process. However, due to the terminology used to describe the process, a lot of developers never evolve beyond the point where they simply write unit tests to verify their code, and thus never experience many of the advantages associated with using tests as a design tool. BDD seeks to ease this realization by focusing on an improved vocabulary. In fact, vocabulary is perhaps the most important aspect of BDD, because it also tries to normalize the vocabulary used by programmers, business developers, testers, and others involved in the development of a system when discussing problems, requirements, and solutions.

Another "double D" is Acceptance Test-Driven Development. In acceptance TDD, development starts by writing automated tests for high level features, based on acceptance tests defined in conjunction with the client. The goal is to pass the acceptance tests. To get there, we can identify smaller parts and proceed with "regular" TDD. In BDD this process is usually centered around user stories, which describe interaction with the system using a vocabulary familiar to everyone involved in the project. BDD frameworks such as Cucumber allow for user stories to be used as executable tests, meaning that acceptance tests can be written together with the client, increasing the chance of delivering the product the client had originally envisioned.

3.1.2 Continuous Integration

Continuous integration is the practice of integrating code from all developers on a regular basis, usually every time a developer pushes code to a remote version control repository. The continuous integration server typically builds all the sources and then runs tests for them. This process ensures that even when developers work on isolated units of features, the integrated whole is considered every time code is committed to the upstream repository. JavaScript does not need compiling, but running the entire test suite for the application on a regular basis can help catch errors early.

Continuous integration for JavaScript can solve tasks that are impractical for developers to perform regularly. Running the entire test suite in a wide array of browser and platform combinations is one such task. Developers working with TDD can focus their attention on a small representative selection of browsers, while the continuous integration server can test much wider, alerting the team of errors by email or RSS.

Additionally, it is common practice for JavaScript to be served minified—i.e., with unneeded white-space and comments stripped out, and optionally local identifiers munged to occupy fewer bytes—to preserve bytes over the wire. Both minifying code too aggressively or merging files incorrectly can introduce bugs. A continuous integration server can help out with these kinds of problems by running all tests on the full source as well as building concatenated and minified release files and re-running the test suite for them.

3.1.3 Asynchronous Tests

Due to the asynchronous nature of many JavaScript programming tasks such as working with XMLHttpRequest, animations and other deferred actions (i.e., any code using setTimeout or setInterval), and the fact that browsers do not offer a sleep function (because it would freeze the user interface), many testing frameworks provide a means to execute asynchronous tests. Whether or not asynchronous unit tests is a good idea is up for discussion. Chapter 12, Abstracting Browser Differences: Ajax, offers a more thorough discussion on the subject as well as an example.

3.1.4 Features of xUnit Test Frameworks

Chapter 1, Automated Testing, already introduced us to the basic features of the xUnit test frameworks: Given a set of test methods, the framework provides a test runner that can run them and report back the results. To ease the creation of shared test fixtures, test cases can employ the setUp and tearDown functions, which are run before and after (respectively) each individual test in a test case. Additionally, the test framework provides a set of assertions that can be used to verify the state of the system being tested. So far we have only used the assert method which accepts any value and throws an exception when the value is falsy. Most frameworks provide more assertions that help make tests more expressive. Perhaps the most common assertion is a version of assertEqual, used to compare actual results against expected values.

When evaluating test frameworks, we should assess the framework's test runner, its assertions, and its dependencies. The Test Runner

The test runner is the most important part of the testing framework because it basically dictates the workflow. For example, most unit testing frameworks available for JavaScript today use an in-browser test runner. This means that tests must run inside a browser by loading an HTML file (often referred to as an HTML fixture) that itself loads the libraries to test, along with the unit tests and the testing framework. Other types of test runners can run in other environments, e.g., using Mozilla's Rhino implementation to run tests on the command line. What kind of test runner is suitable to test a specific application depends on whether it is a client-side application, server-side, or maybe even a browser plugin (an example of which would be FireUnit, a unit testing framework that uses Firebug and is suitable for developing Firefox plugins).

A related concern is the test report. Clear fail/success status is vital to the test-driven development process, and clear feedback with details when tests fail or have errors is needed to easily handle them as they occur. Ideally, the test runner should produce test results that are easily integrated with continuous integration software.

Additionally, some sort of plugin architecture for the test runner can enable us to gather metrics from testing, or otherwise allow us to extend the runner to improve the workflow. An example of such a plugin is the test coverage report. A coverage report shows how well the test suite covers the system by measuring how many lines in production code are executed by tests. Note that 100% coverage does not imply that every thinkable test is written, but rather that the test suite executes each and every line of production code. Even with 100% coverage, certain sets of input can still break the code—it cannot guarantee the absence of, e.g., missing error handling. Coverage reports are useful to find code that is not being exercised by tests.

3.1.5 Assertions

A rich set of assertions can really boost the expressiveness of tests. Given that a good unit test clearly states its intent, this is a massive boon. It's a lot easier to spot what a test is targeting if it compares two values with assertEqual(expected, actual) rather than with assert(expected == actual). Although assert is all we really need to get the job done, more specific assertions make test code easier to read, easier to maintain, and easier to debug.

Assertions is one aspect where an exact port of the xUnit framework design from, e.g., Java leaves a little to be desired. To achieve good expressiveness in tests, it's helpful to have assertions tailored to specific language features, for instance, having assertions to handle JavaScripts special values such as undefined, NaN and infinity. Many other assertions can be provided to better support testing JavaScript, not just some arbitrary programming language. Luckily, specific assertions like those mentioned are easy to write piggybacking a general purpose assert (or, as is common, a fail method that can be called when the assertion does not hold).

3.1.6 Dependencies

Ideally, a testing framework should have as few dependencies as possible. More dependencies increase the chance of the mechanics of the framework not working in some browser (typically older ones). The worst kind of dependency for a testing framework is an obtrusive library that tampers with the global scope. The original version of JsUnitTest, the testing framework built for and used by the Prototype.js library, depended on Prototype.js itself, which not only adds a number of global properties but also augments a host of global constructors and objects. In practice, using it to test code that was not developed with Prototype.js would prove a futile exercise for two reasons:

  • Too easy to accidentally rely on Prototype.js through the testing framework (yielding green tests for code that would fail in production, where Prototype.js would not be available)
  • Too high a risk for collisions in the global scope (e.g., the MooTools library adds many of the same global properties)

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