用视觉语言模型检测安卓应用旋转时的界面状态不一致问题
RotDroid: Cross-Orientation State Equivalence Testing for Detecting GUI Rotation Bugs in Android Apps
- 生成可保持状态的动作序列，实现横竖屏界面等价性验证
- 在真实应用中发现94个未知漏洞，47个被开发者确认修复
- 自建数据集与微调模型，提升跨方向状态比对准确率
屏幕旋转是安卓应用的基本交互方式，但常引发非崩溃型功能缺陷（如布局错乱、状态丢失），难以自动检测。核心挑战在于缺乏可靠的跨方向状态等价性测试依据。本文提出RotDroid框架，通过生成和变异状态保持动作序列（SPS），构建横竖屏间语义等价的界面状态。为支持可靠断言检查，我们构建了包含成对横竖屏界面状态的RotBench数据集，并开发了针对等价性判断微调的RotVL视觉语言模型。在合成与真实数据集上的实验表明，RotVL优于现有先进模型，且在同等预算下比现有技术发现更多旋转引发的缺陷。在开源与闭源应用的大规模研究中，RotDroid共报告94个此前未知的漏洞，其中47个已被开发者确认或修复，验证了其实际有效性。
原文摘要 · Abstract (English)
Screen rotation is a fundamental interaction in Android applications, but it often introduces non-crashing functional failures (NCFs), such as layout inconsistencies and state loss, which are difficult to detect automatically. A key challenge is the lack of effective test oracles for checking cross-orientation state equivalence between portrait and landscape views. We propose RotDroid, a testing framework for detecting GUI rotation bugs via cross-orientation state equivalence. RotDroid generates and mutates State-Preserving action Sequences (SPS) to construct semantically equivalent GUI states across orientations. To support reliable oracle checking, we build RotBench, a dataset of paired portrait-landscape GUI states, and develop RotVL, a vision-language model fine-tuned for equivalence checking. Experiments on both synthetic and real-world datasets show that RotVL outperforms state-of-the-art models, and RotDroid detects more rotation-induced failures than existing techniques under equal budgets. In large-scale studies on open- and closed-source apps, RotDroid reports 94 previously unknown bugs, with 47 confirmed or fixed by developers, demonstrating its practical effectiveness.
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