End-to-end testing of smart TVs has proven to be challenging due to various reasons, such as: the proprietary nature of hardware and software from different TV manufacturers; the difficulty of identifying performance bottlenecks due to visual rendering being performed by cloud-based renderers; etc. As a result, end-to-end testing of a smart TV still relies heavily on time-consuming and costly manual testing. This disclosure describes a framework for end-to-end testing of smart TVs that is automatic, e.g., uses minimal human intervention, and universal (agnostic to TV manufacturer).

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This work is licensed under a Creative Commons Attribution 4.0 License.