AI 中文总结
本文通过系统映射研究梳理2020-2026年5个数据源的33项研究，明确基于AI的软件质量的6类核心挑战，呼吁各方合作制定全面质量评估方法。
AI 中文摘要
人工智能（AI）正越来越多地嵌入现代软件系统，引发了关于应如何定义、评估和保障其质量的重要问题。本文呈现一项针对基于AI的软件质量的系统映射研究（Systematic Mapping Study, SMS），该研究综合了2020年1月至2026年1月间发表的、来自5个电子数据源的主要研究，经自动化搜索、筛选和滚雪球法后共纳入33项主要研究。研究结果识别出6类反复出现的挑战，最突出的挑战是现有质量评估模型存在局限性，其次是非功能性需求管理、质量感知开发及质量保障方面的问题。研究结果呼吁研究人员、工业从业者与标准化组织开展合作，以期可能制定出全面的质量评估及其测量方法。
英文摘要
Artificial Intelligence (AI) is increasingly embedded in modern software systems, raising important questions about how its quality should be defined, assessed, and assured. This paper presents a Systematic Mapping Study (SMS) on the quality of AI-based software. The study synthesizes primary studies published between January 2020 and January 2026 and selected from five electronic data sources. A total of 33 primary studies were included after automated search, screening, and snowballing. The results identify six recurring challenge categories, with the most prominent being limitations in existing quality assessment models, followed by issues in non-functional requirement management, quality-aware development, and quality assurance. The findings suggest a call for collaboration of researchers and industrial practitioners with standardization organizations, that could possibly devise comprehensive quality assessments and their measurement methods.
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