Svetlana Yarosh
Pamela Zave
ABSTRACT
Internet of Things (IoT) frequently involves conflicting interactions between devices and features that must be resolved to a single system state. The problem of feature interaction (FI) resolution has been investigated in Software Engineering through approaches that focus on verifiability but usually do not include the user in the evaluation. This paper bridges the gap between IoT approaches in HCI and Software Engineering by applying qualitative methods to understanding users' mental models of one representative FI resolution mechanism. Our contributions are in identifying common mental model errors and biases and how these may inform future IoT systems and research.
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Index Terms
- Locked or Not?: Mental Models of IoT Feature Interaction
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