一句话：提出用 LLM 将 GUI 测试代码复用为应用专属语音助手，并给出 Android 原型 AppVA 与初步验证。
移动平台上的语音助手多为系统级服务，与应用自身行为脱节，开发者为应用添加语音交互时往往需要手工重新实现应用逻辑，成本高且难以维护。本文提出一种 LLM 驱动的方法，将 GUI 测试代码重新利用为应用行为与对话交互之间的桥梁：测试方法本身编码了保持行为一致、可执行的规范，LLM 将其转换为语音意图、能力描述和可执行动作计划等应用专属语音助手构件，使语音助手直接扎根于既有应用逻辑，而非外部规范。作者以 Android 研究原型 AppVA 展示这一构想，并在五个开源应用上给出初步结果，表明 GUI 测试代码可以超越测试用途，用于合成应用专属语音助手，并揭示了软件测试、交互设计与 LLM 自动化交叉的更大研究方向。
Voice assistants are widely deployed on mobile platforms, yet most are designed as system-level services that remain poorly aligned with application-specific behavior. As a result, enabling voice interaction at the app level requires developers to manually reimplement application logic, leading to high development and maintenance costs. We propose an LLM-driven approach to automating the development of app-specific voice assistants by repurposing GUI test code, which encodes behavior-preserving, executable specifications of application functionality. In this paper, we present a perspective in which large language models reinterpret GUI tests as bridges between application behavior and conversational interaction. By transforming test methods into app-specific VA artifacts, such as voice intents, capability descriptions, and executable action plans, our approach grounds voice assistants directly in existing application logic rather than external specifications. We illustrate this vision through AppVA, a research prototype on Android. Our preliminary results across five open-source applications suggest that GUI test code can be reused beyond testing, enabling the synthesis of app-specific voice assistants and highlighting a broader research direction at the intersection of software testing, interaction design, and LLM-enabled automation.
DOI 原文 · arXiv · PDF（开放获取） · DBLP
@inproceedings{abs-2607-11387,
title = {From GUI Tests to Conversational Interaction: A New Perspective on App-Specific Voice Assistants},
author = {Xue Qin and Sumesh Surendran Letha},
booktitle = {FSE},
year = {2026},
doi = {10.1145/3803437.3805573}
}