arXiv:2607. 11245v2 Announce Type: replace-cross Abstract: To reduce the substantial engineering effort required to test the corresponding applications from Android to OpenHarmony, migrating existing GUI test cases has become a critical problem.
arXiv:2607. 11245v1 Announce Type: cross Abstract: To reduce the substantial engineering effort required to test the corresponding applications from Android to OpenHarmony, migrating existing GUI test cases has become a critical problem.
arXiv:2607. 28750v1 Announce Type: cross Abstract: As mobile applications grow in complexity, traditional End-to-End (E2E) testing frameworks struggle with UI volatility, maintenance overhead, and cross-platform scalability.
The paper introduces DroidTool, a framework that enables Android GUI agents to automatically generate and integrate tool actions—Python functions that manipulate application states—into their hybrid action space. DroidTool follows an agentic workflow with stages of proposal, implementation, test generation, execution, and repair, and it constructs relational tests to ensure comprehensive verification. Experiments on benchmarks such as AndroidWorld, B-MoCA, and MobileSafetyBench show that agents using DroidTool’s self-generated tools outperform GUI-only agents by about 4.47% in performance while reducing interactions by roughly 20.05%.
arXiv:2605. 29486v2 Announce Type: replace-cross Abstract: A central bottleneck for phone-use agents is that controllable, reproducible environments covering real mobile behavior are hard to build at scale.
arXiv:2608. 09273v1 Announce Type: new Abstract: LLMs have demonstrated strong capabilities in code generation and automated program repair, but migrating an entire repository rarely produces a runnable application because long-horizon translation challenges LLM-based agents' ability to maintain repository-level migration objectives.
arXiv:2606. 26707v1 Announce Type: cross Abstract: Adversarial APKs are Android applications modified in the problem space to evade machine-learning malware detectors.
arXiv:2607. 02469v1 Announce Type: cross Abstract: Software tests and code evolve together: a code change should be followed by new or updated tests that record the new software behavior.
ARIA is a multi‑agent large‑language‑model framework that autonomously runs end‑to‑end visual tests on Android infotainment systems. From simple scenario sentences, it executes interactions, generates reproducible scripts, and produces detailed reports with visual evidence. In evaluation on a manufacturer’s device, ARIA achieved a 93.3% completion rate, correctly identified all known defects, and demonstrated lower false‑positive rates compared to a single‑agent baseline.
arXiv:2608. 11588v1 Announce Type: new Abstract: Mobile GUI agents remain brittle when deployed to applications absent from source training.
arXiv:2609.22000v1 Announce Type: new Abstract: Computer-use agents (CUAs) have advanced along two separate lines: graphical interaction and software development through code and the command line. Re...
arXiv:2608. 07775v1 Announce Type: new Abstract: Mobile agents have achieved promising results on clean online benchmarks such as AndroidWorld, yet their performance often degrades sharply in real-world deployment due to environmental variations and imperfect interface conditions.
arXiv:2609.23980v1 Announce Type: cross Abstract: AI agents now report vulnerabilities faster than maintainers can review them. Reports often depend on security properties specific to the application...