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Household smart devices – internet-connected thermostats, lights, door locks, and more – have increased greatly in popularity. These devices provide convenience, yet can introduce issues related to safety, security, and usability. To better understand device owners’ recent negative experiences with widely deployed smart devices and how those experiences impact the ability to provide a safe environment for users, we conducted an online, survey-based study of 72 participants who have smart devices in their own home. Participants reported struggling to diagnose and recover from power outages and network failures, misattributing some events to hacking. For devices featuring built-in learning, participants reported difficulty avoiding false alarms, communicating complex schedules, and resolving conflicting preferences. Finally, while many smart devices support end-user programming, participants reported fears of breaking the system by writing their own programs. To address these negative experiences, we propose a research agenda for improving the transparency of smart devices. 

End-user programming, particularly trigger-action programming (TAP), is a popular method of letting users express their intent for how smart devices and cloud services interact. Unfortunately, sometimes it can be challenging for users to correctly express their desires through TAP. This paper presents AutoTap, a system that lets novice users easily specify desired properties for devices and services. AutoTap translates these properties to linear temporal logic (LTL) and both automatically synthesizes property-satisfying TAP rules from scratch and repairs existing TAP rules. We designed AutoTap based on a user study about properties users wish to express. Through a second user study, we show that novice users made significantly fewer mistakes when expressing desired behaviors using AutoTap than using TAP rules. Our experiments show that AutoTap is a simple and effective option for expressive end-user programming.