基于自定义规则的SysML用例自动生成方法研究

Research on rule-based method for automatic generation of SysML use cases

现代系统越来越复杂,传统的工程方法往往难以处理这些复杂问题。基于模型的系统工程(MBSE)可以通过建立系统模型、对系统进行分析和仿真等方式来快速、准确地掌握系统的行为和性能,从而有效地解决复杂性问题。系统建模语言(SysML)可以帮助人们清晰地理解和描述系统。以往基于自然语言的系统描述方法很容易出现理解歧义以及表达不准确等问题,因此,基于自然语言处理(NLP)技术的SysML图自动生成是目前极具学术价值的研究领域,然而目前关于此方面的研究仍相对有限。本文提出了一种名为NLP驱动的用例图自动生成方法,简称为NLUCD。首先使用事先制定的语言规则对输入文本进行预处理;然后使用NLP工具进行文本分割、词干提取与词形还原等操作;接着使用微调过的BERT模型进行命名实体识别和句法依赖分析;随后,定义了3组规则来提取用例图中的参与者、用例和关系,与用例图中的元素及其关系相对应;最后,绘图工具完成了对SysML用例图的生成。虽然该方法目前主要适用于英文文本,但该方法为系统设计领域的自动化和智能化提供了新思路和新视角,具有一定的理论和实践价值。

Modern systems have become increasingly complex,and traditional engineering methods often struggle to handle these complex problems.Model-based systems engineering(MBSE)could rapidly and accurately grasp system behavior and performance by constructing system models,analyzing and simulating systems,thus effectively addressing complexity problems.The systems modeling language(SysML)can aid in clear understanding and description of systems.Previously,natural language-based system description methods were prone to misunderstandings and inaccurate expression issues.Therefore,SysML diagram automatic generation based on NLP technology is currently a research area with great academic value,but current research in this area is relatively limited.This study proposed a method named natural language-driven use case diagram automatic generation,abbreviated as NLUCD.Firstly,it employed pre-determined language rules to preprocess input text.Then it applied NLP tools for text segmentation,stemming,and lemmatization.Next,it utilized a fine-tuned BERT(bidirectional encoder representations from transformers)model for named entity recognition and syntax dependency analysis.Subsequently,it defined three sets of rules to extract participants,use cases,and relationships in the use case diagram,corresponding to the elements and relationships in the use case diagram.Finally,the drawing tool completed the generation of the SysML use case diagram.Although the proposed method is currently mainly applicable to English text,it provides new ideas and perspectives for the automation and intelligence of the system design field,having both theoretical and practical value.