statement coverage meaning in Chinese
语句覆盖 在一个组件中，通过执行一定的测试用例所能达到的语句覆盖百分比。
Examples
- You can measure code coverage in several ways : by assessing line or statement coverage , condition coverage , branch coverage , and so on
您可以通过许多方法来测量代码覆盖率：通过评估代码行或语句的覆盖面、条件覆盖面、分支覆盖面等等。 - The mcdc , decision and statement coverage tools accurately collect live , in - circuit program measurements , analyze test history at a number of levels of granularity and generate specific reports to document both the process and the results
、决策及语句覆盖工具准确收集运行中的在线程序测量，以多种间隔等级分析测试历史，并生成记录过程和结果的特定报告。 - Many problems in software testing , such as statement coverage and patl1 coverage , can be reduced to tlle path - wise test data generating problem , which will be referred to as problem q in this thesis and can be described ast given a program p and a path w in p , let the input space of p be d , compute x e d , such that when p executes on x , path w wiil be traversed
软件测试中的诸如语句覆盖、路径覆盖等问题可以归结为面向路径的测试数据的生成问题。该问题在本文中简称为问题2 ，可以描述为：给定一个程序p和p中一条路径w ，设p的输入空间为d ，求( ? ) d ，使得p以( - Basic black - box testing and white - box testing are successfully carried out . in white - box testing , the statement coverage and branch coverage are achieved ; static analysis and dynamic analysis are also implemented . the static analysis mainly used to generate flow graph while the dynamic analysis serves program instrument , technique realization object , subprogram and the detailed coverage and the calculation of operation time of the documents
原型系统实现了基本的黑盒和白盒测试,其中白盒测试实现了语句和分支覆盖;实现了汇编测试的静态分析和动态分析,静态分析主要是生成程序的流程图,动态分析主要是利用程序插桩技术实现语句和分支覆盖率及在多个测试用例驱动下的综合覆盖率的计算和运行时间及内存使用情况的统计。 - This method is more computationally efficient than prior efforts to assess observability and it could be integrated into compilers and simulators easily . a new simulation vector generation procedure involving the observability - enhanced statement coverage metric is developed . the method is simulation - based and driven by the distribution of unobserved statements
可观测性语句覆盖率并不像传统的语句覆盖率那样过于乐观，它不仅评估代码是否被执行，而且检验被激励激活的那些潜在错误的影响是否可以传播到观测点，该准则可以更确切地评估验证的力度。