Prior work has developed numerous systems that test the security and safety of smart homes. For these systems to be applicable in practice, it is necessary to test them with realistic scenarios that represent the use of the smart home, i.e., home automation, in the wild. This demo paper presents the technical details and usage of Helion, a system that uses n-gram language modeling to learn the regularities in user-driven programs, i.e., routines developed for the smart home, and predicts natural scenarios of home automation, i.e., event sequences that reflect realistic home automation usage. We demonstrate the HelionHA platform, developed by integrating Helion with the popular Home Assistant smart home platform. HelionHA allows an end-to-end exploration of Helion's scenarios by executing them as test cases with real and virtual smart home devices.

翻译：先前的工作已开发出众多测试智能家居安全性与可靠性的系统。为使这些系统在实践中具有适用性，有必要用代表智能家居实际使用场景（即家庭自动化）的真实案例对其进行测试。本演示论文介绍了Helion的技术细节与使用方式——该系统通过n-gram语言模型学习用户驱动程序（即针对智能家居开发的自动化规则）中的规律性，并预测自然的家庭自动化场景（即反映真实家庭自动化使用情况的事件序列）。我们展示了HelionHA平台，该平台通过将Helion与流行的Home Assistant智能家居平台集成而构建。HelionHA支持对Helion生成的场景进行端到端探索，可将这些场景作为测试用例，在真实及虚拟智能家居设备上执行。