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The previous sections illustrated how easy it is to capture behaviors of varying levels of granularity with easyb. But in order for these specifications to provide the most value, they will need to be executed as a part of the development process and build system.
During a development episode, easyb specifications can be run by setting up an external tool configuration in your IDE or, if you happen to use IntelliJ IDEA, by installing the IntelliJ easyb plugin. The process of getting an external tool up and running varies across IDEs, but generally involves setting up a run configuration that places the easyb JARs on the classpath and then invokes the easyb behavior runner's main method, passing a list of space-separated specifications to run. The IntelliJ plugin simplifies this process by allowing specifications to be run in the same manner as JUnit tests, and provides graphical reporting of results in addition to the behavior runner's console output. Figure 1 below shows the output of executing an easyb story in IntelliJ using the easyb plugin. This story was run just as a JUnit test would have been, and the results of the story are similar in form as well. (Click the image to enlarge it.)
easyb also provides an Ant task and a Maven plugin with which you can run easyb specifications as a part of the build process. These both cause the build to fail if a non-pending specification or story fails, and can optionally generate story reports that contain story narrative and acceptance scenarios apart from the closures that bind them to the system.
Tooling is an important component of any development environment, and the tooling around easyb is already good and grows more and more so each day.
In this brief overview of easyb, you have explored the language's approach to BDD and seen how it helps you think about your system as a collection of behaviors across various levels of granularity. By keeping the focus on behaviors instead of tests for specific classes and methods, BDD -- and easyb -- encourage you to write tests that are more descriptive of what the system should do and less tightly coupled to particular implementations.
Additionally, easyb's approach for capturing user stories is less restrictive than the programmer-oriented syntaxes of comparable tools. easyb aims to stay out of the way of the story-writing process so that the center of attention is on the conversation taking place, not on the tool that is being used to capture that conversation. Furthermore, easyb does make it easy to bind these expressions of behavior to the system under test as a mechanism for validating the conversations.
As easyb draws closer to its 1.0 launch, now is a great time to give it a test drive and see for yourself how BDD and easyb can help you build better systems that more closely match your customers' needs.
Read more about Tools & Methods in JavaWorld's Tools & Methods section.
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