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Combining Model Refinement and Test Generation for Conformance Testing of the IEEE PHD Protocol Using Abstract State Machines

机译:使用抽象状态机结合模型细化和测试生成IEEE PHD协议的一致性测试

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In this paper we propose a new approach to conformance testing based on Abstract State Machine (ASM) model refinement. It consists in generating test sequences from ASM models and checking the conformance between code and models in multiple iterations. This process is applied at different models, starting from the more abstract model to the one that is very close to the code. The process consists of the following steps: (1) model the system as an Abstract State Machine, (2) generate test sequences based on the ASM model, (3) compute the code coverage using generated tests, (4) if the coverage is low refine the Abstract State Machine and return to step 2. We have applied the proposed approach to Antidote, an open-source implementation of IEEE 11073-20601 Personal Health Device (PHD) protocol which allows personal healthcare devices to exchange data with other devices such as small computers and smart phones.
机译:在本文中,我们提出了一种基于抽象状态机(ASM)模型改进的一致性测试方法。它包括生成来自ASM模型的测试序列,并检查多个迭代中的代码和模型之间的一致性。此过程应用于不同的模型,从更靠近代码的抽象模型开始。该过程包括以下步骤:(1)模型作为抽象状态机,(2)基于ASM模型生成测试序列,(3)使用生成的测试计算代码覆盖,(4)如果覆盖范围是低精炼抽象状态机并返回步骤2.我们已应用提出的解毒方法,IEEE 11073-20601个人健康设备(PHD)协议的开源实现,其允许个人医疗设备与其他设备交换数据作为小型计算机和智能手机。

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