# RotDroid: Cross-Orientation State Equivalence Testing for Detecting GUI Rotation Bugs in Android Apps

arXiv: https://arxiv.org/abs/2608.25425 · HTML: https://mlsanity.com/paper/2608.25425/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 13 of its 36 references that are in the map.
- First posted on arXiv 26 Aug 2026.

## Builds on (most cited first, 13 of 13)

- [Qwen3-VL Technical Report](https://mlsanity.com/paper/2511.21631/) (2025)
- [LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models](https://mlsanity.com/paper/2403.13372/) (2024)
- [AutoDroid: LLM-powered Task Automation in Android](https://mlsanity.com/paper/2308.15272/) (2023)
- [Ferret-UI: Grounded Mobile UI Understanding with Multimodal LLMs](https://mlsanity.com/paper/2404.05719/) (2024)
- [Fill in the Blank: Context-aware Automated Text Input Generation for Mobile GUI Testing](https://mlsanity.com/paper/2212.04732/) (2022)
- [Chatting with GPT-3 for Zero-Shot Human-Like Mobile Automated GUI Testing](https://mlsanity.com/paper/2305.09434/) (2023)
- [Deep Reinforcement Learning for Black-Box Testing of Android Apps](https://mlsanity.com/paper/2101.02636/) (2021)
- [Nighthawk: Fully Automated Localizing UI Display Issues via Visual Understanding](https://mlsanity.com/paper/2205.13945/) (2022)
- [Data Loss Detector: Automatically Revealing Data Loss Bugs in Android Apps](https://mlsanity.com/paper/2010.05584/) (2020)
- [Effective, Platform-Independent GUI Testing via Image Embedding and Reinforcement Learning](https://mlsanity.com/paper/2208.09116/) (2022)
- [The Metamorphosis: Automatic Detection of Scaling Issues for Mobile Apps](https://mlsanity.com/paper/2212.04388/) (2022)
- [A Study of Using Multimodal LLMs for Non-Crash Functional Bug Detection in Android Apps](https://mlsanity.com/paper/2407.19053/) (2024)
- [Automated Soap Opera Testing Directed by LLMs and Scenario Knowledge: Feasibility, Challenges, and Road Ahead](https://mlsanity.com/paper/2412.08581/) (2024)

## Abstract (arXiv)

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.