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Cedric Beust to address some of the shortcomings of JUnit and to take advantage of the new features and trends in Java development. TestNG uses JSE 5.0 annotations or Javadoc comments to enable simple POJOs to act as a testing class, as opposed to JUnit s more traditional approach of using inheritance and abstract classes. TestNG supports data-driven testing, acknowledging the fact that a large percentage of tests performed functional and integration tests while only a small percentage are pure unit tests. TestNG also provides an XML-based runtime configuration which, mixed with the ability to classify tests using groups, provides a powerful execution model which eliminates the need to use constructs like JUnit s TestSuite. TestNG is hosted at www.testng.org and is distributed as a single ZIP file. At the time of this writing, version 4.3 is available (testng-4.3.zip). At the root of the archive you ll find JAR files for JDK 1.4 and JDK 1.5. For the TechConf application and the purposes of this chapter, we will use the JDK 1.5 version (testng-4.3-jdk15.jar). This JAR needs to be in your classpath for the exercises in this chapter to work. Let s start first with a simple class to test the Greeter class previously created. In TestNG any simple Java class can become a test class by using metadata annotations. Listing 8-4 shows the TestNG version of the GreeterTest class. Listing 8-4. TestNG Annotated POJO import org.testng.Assert; import org.testng.annotations.Configuration; import org.testng.annotations.Test; public class GreeterTest { private Greeter greeter; @Configuration(beforeTestClass = true) private void init() { greeter = new Greeter(); } @Test public void testGreet() { assert "Hello World".equals(greeter.greet()); } @Test public void testGreetString() { String name = "Michael"; Assert.assertEquals("Hello " + name, greeter.greet(name)); } }
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For the BitArray class shown earlier, the compiler compiles the indexer as though the original source code were written as follows:
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For those of you who are unfamiliar with these types of tools, let me explain what each of them does. An error detection tool looks for invalid memory accesses, invalid parameters to system APIs and COM interfaces, memory leaks, and resource leaks, among other things. A performance tool helps you track down where your application is slow; that spot is invariably somewhere other than where you think it is. A code-coverage tool shows you the source lines not executed when you run your program. Code-coverage information is helpful because if you're looking for a bug, you want to look for it only in lines that are executing. Step 7: Start Heavy Debugging I differentiate heavy debugging from the light debugging I mentioned in Step 4 by what you're doing in the debugger. When you're doing light debugging, you're just looking at a few states and a couple of variables. In contrast, when you're doing heavy debugging, you're spending a good deal of time exploring your program's operation. It is during the heavy debugging stage that you want to use the debugger's advanced features. Your goal is to let the debugger do as much of the heavy lifting as possible. s 6 through 8 discuss the various debuggers' advanced features. Just as when you're doing light debugging, when you're doing heavy debugging, you should have an idea of where you think your bug is before you start using the debugger, and then use the debugger to prove or disprove your hypothesis. Never sit in the debugger and just poke around. In fact, I strongly encourage you to actually write out your hypothesis before you ever fire up the debugger. That will help you keep completely focused on exactly what you're trying to accomplish. Also, when you're doing heavy debugging, remember to regularly review changes you made to fix the bug in the debugger. I like to have two machines set up side by side at this stage. That way I can work at fixing the bug on one machine and use the other machine to run the same code with normal condition cases. The idea is to always double-check and triple-check any changes so you're not destabilizing the normal operation of your product. I'll give you some career advice and let you know that your boss really hates it when you check in code to fix a bug and your product handles only weird boundary conditions and no longer handles the normal operation case. If you set up your project correctly and follow the debugging steps in this chapter and the recommendations in 2, you hopefully won't have to spend much time doing heavy debugging. Step 8: Verify That the Bug Is Fixed When you think you've finally fixed the bug, the next step in the debugging process is to test, test, and retest the fix. Did I also mention that you need to test the fix If the bug is in an isolated module on a line of code called once, testing the fix is easy. However, if the fix is in a core module, especially one that handles your data structures and the like, you need to be very careful that your fix doesn't cause problems or have side effects in other parts of the project. When testing your fix, especially in critical code, you should verify that it works with all data conditions, good and bad. Nothing is worse than a fix for one bug that causes two other bugs. If you do make a change in a critical module, you should let the rest of the team know that you made the change. That way, they can be on the lookout for any ripple effects as well. Debugging War Story: Where Did the Integration Go 19
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A method in the Fax object registers interest with the MailManager s event. A method in the Pager object registers interest with the MailManager s event. A new mail message arrives at MailManager. The MailManager object fires the notification off to all the registered methods, which process the mail message as desired
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As was the case with properties, indexers can implement only the get or set accessor; this provides a read-only or write-only member. As with properties, if the intention is to use the
The Changing Way We Work
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