EpiDroid: Dependency-Guided Recomposition for Deep State Discovery in Mobile GUI Testing
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , , , , , , , , |
|---|---|
| Format: | Preprint |
| Publié: |
2026
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866917380003725312 |
|---|---|
| author | Song, Jiahui Zhi, Jiaxin Zhao, Kangjia Zhi, Chen Han, Junxiao Zhao, Xinkui Wang, Nan Deng, Shuiguang Yin, Jianwei |
| author_facet | Song, Jiahui Zhi, Jiaxin Zhao, Kangjia Zhi, Chen Han, Junxiao Zhao, Xinkui Wang, Nan Deng, Shuiguang Yin, Jianwei |
| contents | The increasing scale and complexity of mobile applications make automated GUI exploration essential for software quality assurance. However, existing methods often neglect state dependencies between test fragments, which leads to redundant exploration and prevents access to deep application states. We introduce EpiDroid, a black-box, pluggable framework that augments existing explorers through semantic state dependency awareness. EpiDroid distills raw traces into stable test fragments to extract underlying dependencies. It then employs a Recomposition-Replay paradigm to perform impact reasoning via LLM and deterministic replay on high-value mutable state elements. Through iterative feedback, EpiDroid refines the state-dependency graph to systematically reach deep application states. We integrated EpiDroid into both industrial and state-of-the-art research tools and evaluated it on 20 real-world apps. The results show that EpiDroid consistently improves the performance of all baselines, increasing average code coverage by 10--28\% and delivering 3--4$\times$ more coverage gain compared to continuing the baselines alone from the same starting point. This demonstrates that dependency-guided recomposition unlocks deep states that forward exploration cannot access, irrespective of additional budget. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_01522 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | EpiDroid: Dependency-Guided Recomposition for Deep State Discovery in Mobile GUI Testing Song, Jiahui Zhi, Jiaxin Zhao, Kangjia Zhi, Chen Han, Junxiao Zhao, Xinkui Wang, Nan Deng, Shuiguang Yin, Jianwei Software Engineering K.6.3 The increasing scale and complexity of mobile applications make automated GUI exploration essential for software quality assurance. However, existing methods often neglect state dependencies between test fragments, which leads to redundant exploration and prevents access to deep application states. We introduce EpiDroid, a black-box, pluggable framework that augments existing explorers through semantic state dependency awareness. EpiDroid distills raw traces into stable test fragments to extract underlying dependencies. It then employs a Recomposition-Replay paradigm to perform impact reasoning via LLM and deterministic replay on high-value mutable state elements. Through iterative feedback, EpiDroid refines the state-dependency graph to systematically reach deep application states. We integrated EpiDroid into both industrial and state-of-the-art research tools and evaluated it on 20 real-world apps. The results show that EpiDroid consistently improves the performance of all baselines, increasing average code coverage by 10--28\% and delivering 3--4$\times$ more coverage gain compared to continuing the baselines alone from the same starting point. This demonstrates that dependency-guided recomposition unlocks deep states that forward exploration cannot access, irrespective of additional budget. |
| title | EpiDroid: Dependency-Guided Recomposition for Deep State Discovery in Mobile GUI Testing |
| topic | Software Engineering K.6.3 |
| url | https://arxiv.org/abs/2604.01522 |