Using @Init and @Destroy in Java

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Listing 315
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Component implementations can receive lifecycle noti cations by annotating public, zero-argument methods with the @Init and @Destroy annotations
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import orgosoascaannotationsScope; import orgosoascaannotationsInit; import orgosoascaannotationsDestroy; @Scope( COMPOSITE ) public class CreditComponent implements CreditService { @Init public void init(){ // perform initialization }
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Composite-scoped implementations can be set to eagerly initialize through use of the @EagerInit annotation
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Eager Initialization By default, composite-scoped implementations are lazily instantiated by the SCA runtime that is, they are instantiated as the rst service request is received In some cases, particularly when initialization is time-consuming, it is useful to perform instantiation upfront as the composite is activated in the domain Compositescoped implementations can be set to eagerly initialize through use of the @EagerInit annotation, as shown in Listing 316
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Listing 316 import import import import
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An Implementation Marked to Eagerly Initialize
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orgosoascaannotationsScope; orgosoascaannotationsEagerInit; orgosoascaannotationsInit; orgosoascaannotationsDestroy;
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@Scope( COMPOSITE ) @EagerInit public class CreditComponent implements CreditService { @Init public void init(){ // perform initialization } @Destroy public void destroy(){ // perform cleanup } // }
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The preceding implementation will be instantiated as soon as the component is activated in the domain, prior to receiving requests As part of the instantiation process, the init method will also be
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invoked by the SCA runtime (The implementation could have omitted an initializer if it were not required)
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We conclude this chapter with a note on testing A common question that arises when writing SCA components is how best to test them In recent years, a wide range of testing methodologies has emerged, some of which have engendered a great deal of controversy Choosing the right methodology, whether it is Test Driven Development (TDD) or a more traditional code- rst approach, is a personal choice and depends on the requirements of a particular project However, whatever approach to testing is adopted, SCA s reliance on inversion of control makes this process much easier How a programming model facilitates testing is of critical importance given the impact it has on project costs As was learned with EJB, programming models that require complex test setup can be one of the primary impediments to developer productivity Tests that are unnecessarily time-consuming to set up take away from development time and hinder the code-test-refactor process that is key to producing good software Moreover, complex setup often leads to poor test coverage, resulting in higher costs later in a project s life cycle If tests are too complex to write and set up, developers will either avoid doing so or not be able to create ones that are ne-grained enough to exercise all parts of an application Poor test coverage will inevitably result in more expensive bug xing after an application has gone into production As an application enters maintenance mode, poor tests will continue to incur signi cant costs Changes and upgrades will be dif cult to verify and take longer to verify all of which is to say that contrary to being relegated to an afterthought, testing strategy should be at the forefront of project planning Further, the extent to which a programming model facilitates or hinders testing will have a direct impact on how successful it is in fostering productivity and cost savings A comprehensive and cost-effective testing strategy will include unit, integration, and functional testing To broadly categorize, unit
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testing involves verifying small units of code, in isolation or with a few collaborating objects In object-oriented languages, a unit of code is commonly a class, which may rely on a few other classes (collaborating objects) Unit tests are run on a developer s machine and periodically on dedicated testing servers Integration testing involves verifying the interaction of various application subsystems and is therefore conducted at a coarser-grained level Integration tests are typically run on dedicated testing servers and not part of the developer build Functional testing entails an even broader scope, verifying application behavior based on end-user scenarios Like integration tests, functional tests are typically run on separate testing servers In the days of CORBA and EJB 20, even unit testing typically required deploying and running the components in a container, often with complex harnesses for setting up required infrastructure This quickly proved to be unwieldy as time-consuming testing hindered fast, iterative development The dif culty of conducting ef cient testing became one of the major drags on developer productivity with these earlier frameworks and a hidden source of signi cant project cost Having learned from this, SCA follows in the footsteps of other IoC frameworks, most notably Spring, in its approach to unit testing By avoiding the use of APIs in all but exceptional circumstances, unit testing SCA components is trivial: Pick your favorite test harness, such as JUnit or TestNG, and instantiate them In other words, verifying behavior is as simple as:
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1 CreditService creditService = new CreditComponent(); 2 int result = creditServicescoreApplicant(applicantID); 3 // verify the result
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Unit testing becomes slightly more involved when collaborating objects are required Take the LoanComponent from the example presented in this chapter: It requires a CreditService One solution would be to simply instantiate a CreditComponent, as shown previously, and pass it to the LoanComponent This, however, can quickly become unmanageable if the CreditComponent requires other services, which themselves depend on additional services, and so on
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