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PARADIGM-COV: A multimensional test coverage analysis tool

机译:PARADIGM-COV:多维测试覆盖率分析工具

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摘要

Currently, software tends to assume increasingly critical roles in our society so assuring its quality becomes ever more crucial. There are several tools and processes of software testing to help increase quality in virtually any type of software. One example is the so called Model-Based Testing (MBT) tools, that generate test cases from models. However, most of these tools have a configuration phase, where test input data is provided manually by the tester, which influences the quality of the test suite generated. By adding coverage analysis to MBT tools it is possible to give feedback and help the tester to define the configuration data needed to achieve the most valuable test suite as possible. This paper presents a tool, PARADIGM-COV, that produces coverage information both over the PARADIGM model elements (to assess if input data is adequate to cover the test goals and assess if preconditions are achievable), and during test case execution (to identify the parts of the model/code that were actually exercised).
机译:当前,软件倾向于在我们的社会中扮演越来越重要的角色,因此确保软件的质量变得越来越重要。有几种软件测试工具和过程可以帮助提高几乎任何类型的软件的质量。一个示例就是所谓的基于模型的测试(MBT)工具,该工具可以从模型生成测试用例。但是,大多数这些工具都具有配置阶段,其中测试人员手动提供测试输入数据,这会影响生成的测试套件的质量。通过将覆盖率分析添加到MBT工具中,可以给出反馈并帮助测试人员定义实现尽可能有价值的测试套件所需的配置数据。本文介绍了一个工具PARADIGM-COV,它可以在PARADIGM模型元素上(用于评估输入数据是否足以覆盖测试目标并评估是否可以满足前提条件)以及在测试用例执行期间生成覆盖信息。实际执行的模型/代码部分)。

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