Working with Merged Code Coverage Data.
使用合并的代码覆盖率数据。
Coverage data helps identify obsolete tests that can be dropped.
覆盖率数据可以帮助识别能被遗弃的无用数据。
Coverage data detects this situation promptly so it can be corrected.
覆盖率数据能够迅速的发现这种情况，所以它能够被校正。
You do this by configuring test runs to produce code coverage data.
这项测量可以透过设定测试回合以产生程式码涵盖范围资料来达成。
But once you've collected all that coverage data, what can you do with it?
但是一旦您收集了所有的覆盖率数据，您可以对它们做些什么呢？
Accumulating coverage data from runs of both automated and manual tests, and.
既能从自动测试、又能从手动测试收集覆盖率数据。
Don't limit your use of coverage data to a single number at the top of the summary.
不要在总结的顶部，限制您对覆盖率数据的使用为单个号码。
This topic describes how to merge code coverage data and view that merged data.
本主题描述如何合并代码覆盖率数据以及查看合并的数据。
If the program's binaries are instrumented, code coverage data will be gathered.
如果这个程序的二进制文件经过了检测，则将收集代码覆盖率数据。
To obtain code coverage data, the assembly being tested must first be instrumented.
要获取代码覆盖率数据，必须先“检测”所测试的程序集。
Try the automated report scripts and find out how coverage data can help you manage your project.
试着将报表脚本自动化，并弄清覆盖率数据是怎样帮助您管理您的项目的。
The screen shot in Figure 3 shows the coverage data produced by running the tests on one solution.
图3中显示的是在一个解决方案中通过运行测试产生的覆盖数据。
The instrumentation process adds code to the assembly so that code coverage data can be generated.
检测程序会将程序码加入至组件，以便产生程序码涵盖范围资料。
The PureCoverage export format is in ASCII and is used to transfer coverage data to other programs.
PureCoverage输出格式是ASCII形式的，并用于将覆盖率数据转化为其他的项目。
This XML file contains all the merged code coverage data, which you can see if you re-import the file.
此xml档会包含所有合并的程序码涵盖范围资料，只要您再次汇入该档案即可检视那些资料。
For code coverage data to appear in the report, team members must instrument tests to gather that data.
若要在报表中显示程序码涵盖范围资料，小组成员必须设定测试来收集该资料。
Likewise, managers can use coverage data to better estimate the time a developer actually needs to do the work.
同样，管理人员可以使用覆盖数据更好地估计开发人员实际所需的时间。
The output includes coverage percentages, graphs, and overview pages that allow quick browsing of coverage data.
输出包括覆盖率百分比、图表以及概述页，可以快速浏览覆盖率数据。
Test result data, including code coverage data, is stored in XML format only when you explicitly export it.
只有当您明确地汇出测试结果资料 （包括程式码涵盖范围资料） 时，它才会以XML格式储存。
NET test runs, code coverage data can be gathered when other binary files are tested, including DLLs that your ASP.
NET测试回合期间，在测试其他二进位档案时可以收集程序码涵盖范围资料，包括您的ASP。
Coverage reports are the most basic of PureCoverage reports; they present the coverage data itself rather than any analysis.
覆盖率报告是大多数PureCoverage报告的基础，它们呈现的是覆盖率数据本身，而不是任何的分析数据。
You also have the ability to convert files containing exported coverage data into a form that can be viewed in a Web browser.
您还可以将一个包含了输出覆盖率数据的文件，转化为可以在Web浏览器中浏览的形式。
An example would be if two users start test runs and also request code coverage data from the same assembly at the same time.
例如，有两个使用者启动测试回合，也在同一时间从同一个组件要求程序码涵盖范围资料。
The only reason to export code coverage data as an XML file is to save the results of merging multiple code-coverage results.
将程式码涵盖范围资料汇出为XML档的唯一理由，是为了储存合并多个程式码涵盖范围结果的结果。
Figure 2 shows a low coverage report that lists the source files with coverage data in myprog.pcv that have less than 75% coverage.
图2显示了一个列出了源文件的覆盖率报告，它还带有myprog . pc v中不超过75%覆盖率的覆盖率数据。
You can also work with code coverage data in other ways, such as by saving merged data to disk and re-importing it to view it later.
您还可以通过其他方式使用代码覆盖率数据，例如将合并的数据保存到磁盘中并将其重新导入以便以后查看。
This walkthrough illustrates how to view code coverage data, which shows the proportion of your project's code that is being tested.
此演练说明如何查看代码覆盖率数据，这些数据显示正在测试的项目代码占所有代码的比例。
Importing XML data - If you import Code coverage data from an XML file, you can only see statistics for line coverage, not block coverage.
汇入xml资料：如果您从XML档案汇入程序码涵盖范围资料，则只会看到程序码行涵盖范围的统计资料，而非程序码区块涵盖范围的统计资料。
Coverage data for child and maternal health services in 28 sub-Saharan African countries were obtained from the 2000-2008 Demographic health Survey.
撒哈拉以南28个非洲国家的妇幼保健服务覆盖情况的数据从2000- 2008年间的“人口健康调查”获得。
By using these specialized reports it is possible to use code coverage data to detect some common types of problems that many teams encounter. For example.
通过使用这些特定的报告，使用这些代码覆盖率数据，以探测许多团队可能会碰到的一些共同类型的问题。
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