AI 中文总结
本研究通过比较五种移动开发实现，揭示跨平台与原生开发在软件质量上的权衡，强调优势与成本取决于质量属性、工作负载、平台和测量边界。
AI 中文摘要
跨平台移动框架承诺代码复用、更短的交付周期和更低的实现成本，但其相对于原生开发的权衡仍难以客观评估。许多比较依赖于简化的应用、不一致的功能集或狭窄的指标集。本文比较了同一植物管理应用的五种实现：原生iOS、原生Android、Flutter、React Native和Kotlin Multiplatform。共享方法同时针对Android和iOS，产生八个可执行变体。在ISO/IEC 25010的指导下，研究考察了时间行为、实现占用、源代码组织和可观察的渲染响应性。所有实现共享相同的领域、后端服务、功能需求和基准契约。提供的数据集包含每个变体2000次完成的运行，涵盖认证和缓存检索、图像传输和解码、列表渲染和滚动、本地同步以及媒体上传。后端准备和框架特定的UI驱动程序与主要客户端工作流分开分析。原生在两个操作系统上记录最低的非UI客户端小计，Kotlin Multiplatform是最接近的跨平台实现，而操作和UI包装器排名因任务而异。共享方法包含的原生移动源代码少于原生应用组合，源代码清单显示文件大小、组织和依赖使用的不同模式。该研究并非确定普遍优越的技术，而是表明每种方法的优势和成本取决于质量属性、工作负载、平台和测量边界。
英文摘要
Cross-platform mobile frameworks promise code reuse, shorter delivery cycles, and lower implementation effort, but their trade-offs relative to native development remain difficult to assess objectively. Many comparisons rely on simplified applications, inconsistent feature sets, or a narrow set of metrics. This paper compares five implementations of the same plant-management application: native iOS, native Android, Flutter, React Native, and Kotlin Multiplatform. The shared approaches target both Android and iOS, yielding eight executable variants. Guided by ISO/IEC 25010, the study examines time behavior, implementation footprint, source-code organization, and observable rendering responsiveness. All implementations share the same domain, backend services, functional requirements, and benchmark contract. The supplied dataset contains 2,000 completed runs per variant and covers authenticated and cached retrieval, image transfer and decoding, list rendering and scrolling, local synchronization, and media upload. Backend preparation and framework-specific UI drivers are analyzed separately from the primary client workflow. Native records the lowest non-UI client subtotal on both operating systems, with Kotlin Multiplatform the closest cross-platform implementation, while operation and UI-wrapper rankings vary by task. The shared approaches contain less authored mobile source than the native applications combined, and the source inventory shows different patterns of file size, organization, and dependency use. Rather than identifying a universally superior technology, the study shows that each approach's advantages and costs depend on the quality attribute, workload, platform, and measurement boundary.
Comments19 pages, 1 figure, 8 tables, 4 charts
