  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.
