完整的IOCO测试用例:案例研究

S. C. Paiva, A. Simão, M. Varshosaz, M. Mousavi
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引用次数: 4

摘要

在基于模型的测试中,输入/输出转换系统(IOTSs)作为测试模型被广泛使用。传统上,输入输出一致性测试(IOCO)被用于从iots生成随机测试用例。最近一种用于iots的测试用例生成方法称为Complete IOCO,它应用故障模型来获得具有保证iots故障覆盖的完整测试套件。本文测量了完全IOCO的效率,并与JTorX工具中实现的传统IOCO测试用例生成进行了比较。为此,我们使用了一个案例研究,涉及来自汽车和铁路领域的五个规范模型。为了比较两种测试生成方法杀死它们的效率,产生了规格的错误突变。结果表明,完全IOCO在大状态空间检测深断层时效率更高,而在小状态空间检测浅断层时效率更高。
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Complete IOCO test cases: a case study
Input/Output Transition Systems (IOTSs) have been widely used as test models in model-based testing. Traditionally, input output conformance testing (IOCO) has been used to generate random test cases from IOTSs. A recent test case generation method for IOTSs, called Complete IOCO, applies fault models to obtain complete test suites with guaranteed fault coverage for IOTSs. This paper measures the efficiency of Complete IOCO in comparison with the traditional IOCO test case generation implemented in the JTorX tool. To this end, we use a case study involving five specification models from the automotive and the railway domains. Faulty mutations of the specifications were produced in order to compare the efficiency of both test generation methods in killing them. The results indicate that Complete IOCO is more efficient in detecting deep faults in large state spaces while IOCO is more efficient in detecting shallow faults in small state spaces.
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