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.
arXiv:2509. 24148v3 Announce Type: replace-cross Abstract: Test-Driven Development (TDD) is a widely adopted practice that requires developers to create and execute tests alongside implementation.
arXiv:2607. 28645v1 Announce Type: cross Abstract: Recent multimodal large language models can convert visual designs directly into executable code, but real mobile products require multiple screenshots to become a buildable codebase with shared components and working navigation.
arXiv:2606. 12817v1 Announce Type: new Abstract: Understanding the digital world on mobile devices is shifting from static UI perception to dynamic action comprehension.
arXiv:2606. 12817v2 Announce Type: replace Abstract: Understanding the digital world on mobile devices is shifting from static UI perception to dynamic action comprehension.
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:2511. 02399v3 Announce Type: replace-cross Abstract: Recent advances in large language model agents offer the promise of automating end-to-end software development from natural language requirements.
arXiv:2604. 01527v4 Announce Type: replace-cross Abstract: Production deployment of AI coding agents requires fast, reproducible evaluation signals.
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:2604. 06742v2 Announce Type: replace-cross Abstract: The evolution of Large Language Models (LLMs) has catalyzed a paradigm shift towards intent-driven software development, where autonomous agents are expected to design and deliver complete, runnable software systems from scratch.
arXiv:2607. 16388v1 Announce Type: cross Abstract: Large-scale AI datacenter platforms comprise thousands of heterogeneous hardware components whose validation requires comprehensive fault injection test plans.
arXiv:2607. 13465v1 Announce Type: cross Abstract: LLM-based agents have rapidly improved at operating individual digital environments such as mobile applications, desktop systems, and smart homes.
arXiv:2608. 16742v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved remarkable progress in code generation, yet ensuring correctness in complex, repository-level tasks remains challenging.