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arXiv 1504.02441cs.LO
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概率自动机的Ioco理论

Ioco Theory for Probabilistic Automata

Marcus Gerhold, Mariëlle Stoelinga

摘要:

基于模型的测试(MBT)是一种众所周知的技术,它允许自动生成测试用例,执行和评估。为了测试非功能属性,已经开发了一些测试MBT框架来测试具有实时、连续行为、符号数据和定量系统方面的系统。值得注意的是,这些框架中有很多是基于Tretmans的经典输入/输出一致性(IOCO)框架。然而,基于模型的测试理论处理概率行为还不存在。概率在许多不同的系统中起着重要的作用:不可靠的通信信道,随机算法和通信协议,服务水平协议牵制了正常运行时间的百分比,等等,因此,概率测试理论是非常重要的实际意义。我们提出了ioco的概率变体的成分,并定义了πoco关系,表明它保守地扩展了ioco,并定义了测试用例,执行和评估的概念。

英文摘要:

Model-based testing (MBT) is a well-known technology, which allows for automatic test case generation, execution and evaluation. To test non-functional properties, a number of test MBT frameworks have been developed to test systems with real-time, continuous behaviour, symbolic data and quantitative system aspects. Notably, a lot of these frameworks are based on Tretmans' classical input/output conformance (ioco) framework. However, a model-based test theory handling probabilistic behaviour does not exist yet. Probability plays a role in many different systems: unreliable communication channels, randomized algorithms and communication protocols, service level agreements pinning down up-time percentages, etc. Therefore, a probabilistic test theory is of great practical importance. We present the ingredients for a probabilistic variant of ioco and define the πoco relation, show that it conservatively extends ioco and define the concepts of test case, execution and evaluation.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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