Xun Qian, Tianyi Wang, Xuhai Xu, Tanya R. Jonker, Kashyap Todi
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引用次数: 0
摘要
无处不在的计算技术的进步使得终端用户能够编写情境感知策略(CAP),根据用户和环境的特定情境来控制智能设备。然而,准确地编写 CAP 并避免运行时出错对终端用户来说是一项挑战,因为很难预见 CAP 在复杂的现实世界条件下的行为。我们提出了一种基于扩展现实(XR)的创作工作流程--Fast-Forward Reality,通过模拟单元测试案例验证 CAP 的行为,使最终用户能够反复创作和完善 CAP。我们开发了一种计算方法,可根据撰写的 CAP 和用户的上下文历史自动生成测试用例。我们的系统在 XR 中以身临其境的可视化方式提供每个测试用例,方便用户验证 CAP 行为并确定必要的改进。我们在一项用户研究(N=12)中对 Fast-Forward Reality 进行了评估。我们的编写和验证流程提高了 CAP 的准确性,用户对系统的可用性给予了积极反馈。
Fast-Forward Reality: Authoring Error-Free Context-Aware Policies with Real-Time Unit Tests in Extended Reality
Advances in ubiquitous computing have enabled end-user authoring of context-aware policies (CAPs) that control smart devices based on specific contexts of the user and environment. However, authoring CAPs accurately and avoiding run-time errors is challenging for end-users as it is difficult to foresee CAP behaviors under complex real-world conditions. We propose Fast-Forward Reality, an Extended Reality (XR) based authoring workflow that enables end-users to iteratively author and refine CAPs by validating their behaviors via simulated unit test cases. We develop a computational approach to automatically generate test cases based on the authored CAP and the user's context history. Our system delivers each test case with immersive visualizations in XR, facilitating users to verify the CAP behavior and identify necessary refinements. We evaluated Fast-Forward Reality in a user study (N=12). Our authoring and validation process improved the accuracy of CAPs and the users provided positive feedback on the system usability.