一句话：提出PropGen，用LLM从GUI状态推断并验证应用功能，合成与精化属性以自动进行移动应用属性测试。
移动应用常存在不导致崩溃但功能错误的缺陷，因缺少显式测试预言而难以被传统自动测试发现；属性测试可通过属性描述预期行为来暴露此类缺陷，但手工编写属性困难且昂贵。本文提出PropGen，利用大语言模型自动化移动应用属性测试中的属性构建。它从GUI状态推断候选应用功能假设，执行假设以收集行为证据，从证据合成属性，并基于测试反馈精化不精确属性。在12个真实Android应用上评估：PropGen推断出1210个有效功能并正确执行977个，优于基线的491和187；生成985条属性，其中912条有效，并成功精化127条不精确属性中的118条；最终发现25个此前未知的功能缺陷，许多被现有测试技术遗漏。
Mobile apps often suffer from functional bugs that do not cause crashes but instead manifest as incorrect behaviors under specific user interactions. Such bugs are difficult to detect by conventional automatic testing techniques because they often lack explicit test oracles. Property-based testing can effectively expose them by specifying intended behavior as properties and checking them under diverse interactions. However, its practical use is limited by the reliance on manually written properties, which are difficult and expensive to construct. To address this limitation, this paper explores the use of large language models (LLMs) to automate property construction for property-based testing of mobile apps. This is challenging in two ways. First, it is difficult to systematically uncover and execute diverse app functionalities. Second, it is difficult to derive valid properties from functionality execution results. To address these challenges, we introduce PropGen, which infers candidate app functionalities as hypotheses from GUI states, validates each hypothesis by executing it to collect behavioral evidence, synthesizes properties from the collected evidence, and refines imprecise properties based on testing feedback. We implemented PropGen and evaluated it on 12 real-world Android apps. The results show that PropGen can effectively identify and execute app functionalities, generate valid properties, and refine most imprecise ones. Across all apps, PropGen inferred 1,210 valid functionalities and correctly executed 977 of them, compared with 491 and 187 for the baseline. It generated 985 properties, 912 of which were valid, and successfully refined 118 of 127 imprecise ones exposed during testing. Using the resulting properties, we found 25 previously unknown functional bugs, many of which were missed by existing testing techniques.
@inproceedings{paperbot12227,
title = {PropGen: Automated Property Generation for Property-Based Testing of Mobile Apps},
author = {Yiheng Xiong and Shiwen Song and Bo Ma and Ting Su and Xiaofei Xie},
booktitle = {ASE},
year = {2026},
doi = {10.1145/3832783.3837536}
}