GCov代码覆盖显示和注释。
我主要从单元测试的角度来看代码覆盖。
I'll be looking at code coverage mainly from the standpoint of unit testing.
PureCoverage进行代码覆盖的分析。
代码覆盖是一种查看一套测试覆盖了多少代码的方法。
Code coverage is a way of seeing how much code is covered by a set of tests.
现在所使用的新工具为内核提供了代码覆盖分析的功能。
New tools are now being used that instrument the kernel in such a way that code coverage analysis can be performed.
重要运行时参数的度量，包括内存使用、性能和代码覆盖。
Measurement of vital runtime parameters, including memory usage, performance, and code coverage.
对代码进行测试的下一步是用代码覆盖工具对测试进行度量。
The next step beyond testing code is measuring the tests with a code coverage tool.
那么，代码覆盖与classworking有什么关系呢？
其他的视图帮助使用者定位在配置运行期间，代码覆盖的间隔。
Other views help users locate gaps in code coverage during profiling runs.
图7：RAD修饰词源码视图显示测试代码覆盖论题。
Figure 7: RAD Annotated Source view revealing test coverage issues.
不幸的是，代码覆盖测试只能确保您想要测试的所有代码得到执行。
Unfortunately, code coverage testing only makes sure you're executing all the code you'd like to test.
您还可以通过各种外部工具来生成跟踪，比如探查器和代码覆盖工具。
You can also generate a trace through external tools such as profilers and code-coverage tools.
这些步骤还能使我在开发期间跟踪代码覆盖情况，从而构建更加丰富的规范。
The small steps also let me keep up with my code coverage as I develop, and build a richer specification.
生成分部类，用于书写自定义代码，以避免被自动生成的代码覆盖。
Generates partial classes where custom code can be written and won't be overwritten.
Gretel超越大多数其他代码覆盖工具的地方是它对增量覆盖检查的支持。
Where Gretel goes beyond most other code coverage tools is in its support of incremental coverage checking.
检查传出耦合的关系数据，并将其与代码覆盖相关联，会促进作出更明智的决策。
Examining efferent coupling's relationship data and relating it to code coverage facilitates smarter decision making.
正如您看到的，使用一个代码覆盖工具可以揭露重要的没有相应测试案例的代码。
As you can see, using a code coverage tool can uncover important code that doesn't have a corresponding test case.
它可以发现其他工具不能发现的代码覆盖不足，这会直接变成发现和修复bug。
It finds gaps in code coverage no other tool can, which translates directly into finding and fixing bugs.
如果我们的测试是为了实现较好的代码覆盖，那么必须能够控制人工任务的结果。
If our tests are to achieve good code coverage, then we must be able to control the result of human tasks. Hence, the need for the following requirement.
这个修改后测试用例的所有方面都可以获得通过，包括Hansel代码覆盖检查。
This modified test case passes on all fronts, including the Hansel code coverage checks.
Jaxen有一个基于JUnit的测试套件，而且这个套件的代码覆盖并不完善。
Jaxen has a JUnit-based test suite, though the suite has less-than-perfect coverage.
与Clover这类传统的代码覆盖工具不同，Jester不去查看报告了哪行代码。
Unlike a traditional code coverage tool such as Clover, Jester doesn't watch which lines of code have been executed.
当代码覆盖能够反映出你的测试代码确实正按你命令行事的时候，它们是有用的。
Code coverage is useful in that it shows you that your tests do what you think they do.
为了看看上述测试在检验这块代码时效果如何，我可以用Hansel检查代码覆盖情况。
To see just how effective my tests are at exercising the code, I can check code coverage with Hansel.
它提供了一系列工具用来显示内存泄漏和性能瓶颈，并提供对每一行代码进行代码覆盖的策略。
It offers a suite of utilities that exposes memory leaks and performance bottlenecks, and provides code coverage statistics down to individual lines of code.
很自然，这些工具可通过使用Rational工具来弥补在测试、调优和代码覆盖上的缺乏。
Naturally, these would be supplemented with Rational's tools for testing, profiling, and code coverage.
单元测试并不是惟一用得着代码覆盖工具的地方，但是代码覆盖工具主要还是用在这里。
Unit testing isn't the only scenario where code coverage tools are useful, but it's certainly a major use case.
但是，用Eclipse内的代码覆盖工具运行RMock测试时会带来一些问题(参见表1)。
There are some issues, however, when it comes to running RMock tests with code coverage inside Eclipse (see Table 1).
当测试材料遇到这些钩子时，代码覆盖工具使用这些钩子来记录每个测试在其执行时所经历的过程。
As the test material is run against it, the code coverage tool USES these hooks to log the journey each test takes as it executes.
PureCoverage追踪代码覆盖，因此您可以发现测试与运行时分析工具不能发现的鸿沟。
PureCoverage tracks code coverage, so you can identify gaps in your testing and areas of your program that the runtime analysis tools are not seeing.
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