摘要:非功能需求描述系统质量相关的属性，是软件设计决策的重要依据和评估标准.与功能需求的描述相比，非功能需求描述通常比较分散，且往往是隐含的.当采集到的需求原始描述内容较多时，逐一进行人工判别和整理需要耗费大量的时间和精力.针对中文自然语言描述的需求文本，提出了自动化的非功能需求识别和分类方法.其中，识别过程旨在从文本中提取出可能包含非功能需求的语句，尽可能地缩小人工检查的范围.分类过程则进一步将包含非功能需求的语句划分到性能、可靠性、可用性、安全性、可维护性这五大类非功能需求类型之中.分类训练和实验测试基于课题组工作项目整理的实验数据集进行，最终，基于一个工业界的实际应用案例数据，验证了方法的有效性.



Abstract:Non-functional requirements state quality related expectations to a system, is used as important criteria for software design decision making and design evaluation. Comparing to functional requirements descriptions, non-functional requirements statements are often scattered and implicit, which may require much effort to group and interpret manually. This study proposes an automated non-functional requirements recognition and classification approach, which identifies the sentences that are likely to include information about non-functional requirements, to save manual efforts. Then, given non-functional requirements statement is classified into five possible non-functional requirements types, including:performance, reliability, usability, security, and maintainability. The training of classification model and experiment are based on a requirements dataset from the past projects, and then the proposed approach is validated with an industrial project requirements data.



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