基于限定中文自然语言需求的SysML模型自动生成方法

模型驱动开发方法逐渐成为安全关键信息物理融合系统(safety-critical cyber-physical system,SC-CPS)设计与开发的重要手段.然而,安全关键信息物理融合系统需求往往是通过自然语言描述的,如何自动化或半自动化链接自然语言需求和基于模型驱动的系统设计与开发过程是目前面临的重要挑战.面向安全关键信息物理融合系统,提出基于限定中文自然语言需求的SysML模型自动生成方法RNL2SysML.首先,为了降低自然语言需求表达的二义性,提出一种结构化的限定自然语言需求模板进行需求规约,并通过基于人工智能的(AI)安全关键信息物理融合系统术语提取和推荐方法,对系统需求中的领域术语和数据字典加以自动提取,提高限定自然语言需求规约工作的自动化程度.然后,给出限定自然语言需求规约到SysML系统设计模型的转换方法.最后,基于开源工具Papyrus对所提方法进行了原型工具实现,并通过航空领域的飞机空气增压系统(airplane air compressor system)案例验证了方法的有效性和实用性.

An Automated Approach to Generate SysML Models from Restricted Natural Language Requirements in Chinese

Model-driven development has been gradually adopted as an important approach of designing and developing safety-critical cyber-physical systems(SC-CPSs).The requirement of SC-CPSs is often described in natural language.How to link natural language requirements and the model-driven design and development process of SC-CPSs automatically or semi-automatically is a main existing challenge.In this paper,a method named RNL2SysML is proposed for the automatic generation of SysML models from restricted natural language requirements in Chinese.Firstly,in view of the problem that glossaries need to be manually extracted,a method for extracting and recommending terms of SC-CPSs based on artificial intelligence is proposed.Secondly,in order to reduce the ambiguity of natural language requirements,a restricted natural language requirement template is proposed for requirement specification.Then,the method of transformation from natural language requirement specification to SysML model is given.Finally,based on the open source tool Papyrus,the plugin for the method proposed in this paper is implemented,and the effectiveness and practicality of the method is evaluated and proved by an industry case of the airplane air compressor system in the aviation field.