AI coding agents are increasingly contributing to software development, yet their impact on mobile development has received little empirical attention. In this paper, we present the first category-level empirical study of agent-generated code in open-source mobile app projects. We analyzed PR acceptance behaviors across mobile platforms, agents, and task categories using 2,901 AI-authored pull requests (PRs) in 193 verified Android and iOS open-source GitHub repositories in the AIDev dataset. We find that Android projects have received 2x more AI-authored PRs and have achieved higher PR acceptance rate (71%) than iOS (63%), with significant agent-level variation on Android. Across task categories, PRs with routine tasks (feature, fix, and ui) achieve the highest acceptance, while structural changes like refactor and build achieve lower success and longer resolution times. Furthermore, our evolution analysis shows improvement in PR resolution time on Android through mid-2025 before it declined again. Our findings offer the first evidence-based characterization of AI agents effects on OSS mobile projects and establish empirical baselines for evaluating agent-generated contributions to design platform aware agentic systems.

翻译：AI编码代理正日益参与软件开发，但其对移动开发的影响尚缺乏实证研究。本文首次对开源移动应用项目中代理生成代码进行了类别层面的实证研究。我们利用AIDev数据集中193个经过验证的Android与iOS开源GitHub仓库的2,901个AI撰写的拉取请求（PR），分析了跨移动平台、代理类型和任务类别的PR接受行为。研究发现：Android项目接收的AI撰写PR数量是iOS的2倍，且PR接受率（71%）高于iOS（63%），其中Android平台在不同代理间存在显著差异。在任务类别方面，常规任务（功能、修复和界面类）的PR接受率最高，而重构和构建等结构性变更的成功率较低且解决时间更长。此外，我们的演进分析表明，Android平台的PR解决时间在2025年中之前持续改善，之后再次下降。本研究首次基于实证证据揭示了AI代理对开源移动项目的影响特征，并为评估代理生成代码的贡献、设计具备平台感知能力的代理系统建立了实证基准。