发表机构
Beihang University（北京航空航天大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
RotDroid是一款检测Android应用GUI旋转漏洞的测试框架，通过生成SPS、构建RotBench数据集及开发RotVL模型，在相同预算下比现有技术检测到更多旋转故障，还发现94个未知漏洞且47个被确认修复。
AI 中文摘要
屏幕旋转是Android应用的基础交互方式，但常引发非崩溃性功能故障（NCF），如布局不一致、状态丢失，这类故障难以自动检测。核心挑战是缺乏验证竖屏与横屏视图间跨方向状态等价性的有效测试预言机。我们提出RotDroid，一款通过跨方向状态等价性检测GUI旋转漏洞的测试框架。RotDroid生成并变异状态保留动作序列（SPS），以构建跨方向语义等价的GUI状态。为支持可靠的预言机检查，我们构建了由配对竖屏-横屏GUI状态组成的数据集RotBench，并开发了针对等价性检查微调的视觉语言模型RotVL。在合成数据集与真实数据集上的实验表明，RotVL的性能优于现有最优模型，且在相同预算下，RotDroid检测到的旋转引发故障比现有技术更多。在对开源与闭源应用的大规模研究中，RotDroid报告了94个此前未知的漏洞，其中47个已被开发者确认或修复，证明了其实用有效性。
英文摘要
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.
CommentsAccepted to ISSRE 2026 Research Track
