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Trace2TAP: Synthesizing Trigger-Action Programs from Traces of Behavior.

, , , , , , and . Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 4 (3): 104:1-104:26 (2020)

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Helping Users Debug Trigger-Action Programs., , , , and . Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 6 (4): 196:1-196:32 (2022)Visualizing Differences to Improve End-User Understanding of Trigger-Action Programs., , , , and . CHI Extended Abstracts, page 1-10. ACM, (2020)AutoTap: synthesizing and repairing trigger-action programs using LTL properties., , , , , and . ICSE, page 281-291. IEEE / ACM, (2019)Prototyping Energy Harvesting Powered Systems with Nonvolatile Processor (Invited Paper)., , , , , and . RSP, page 49-55. IEEE, (2018)Learning from Long-Tailed Noisy Data with Sample Selection and Balanced Loss., , and . CoRR, (2022)An extensible system simulator for intermittently-powered multiple-peripheral IoT devices., , , and . ENSsys@SenSys, page 1-6. ACM, (2018)Understanding Trigger-Action Programs Through Novel Visualizations of Program Differences., , , , , and . CHI, page 312:1-312:17. ACM, (2021)When Smart Devices Are Stupid: Negative Experiences Using Home Smart Devices., , , , and . IEEE Symposium on Security and Privacy Workshops, page 150-155. IEEE, (2019)Trace2TAP: Synthesizing Trigger-Action Programs from Traces of Behavior., , , , , , and . Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 4 (3): 104:1-104:26 (2020)