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| 赵梦瑶,陈小红,孙海英,刘静,陈良育,周庭梁.轨道交通联锁领域特定语言的形式化.软件学报,2020,31(6):1638-1653 |
| 轨道交通联锁领域特定语言的形式化 |
| Formalizing Railway Interlocking Domain Specific Language |
| 投稿时间：2019-08-20 修订日期：2019-10-23 |
| DOI：10.13328/j.cnki.jos.005997 |
| 中文关键词: 联锁系统|模板重用|形式化建模|随机混成自动机|领域特定语言 |
| 英文关键词:interlocking system|template reuse|formal modeling|stochastic hybrid automata (SHA)|domain specific language |
| 基金项目:国家重点研发计划（2018YFB2101300）；国家自然科学基金（61332008，91418203，61672230，61572195，11471209，61802251）；上海市经济和信息化委员会专项资金（160306） |
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| 摘要点击次数: 508 |
| 全文下载次数: 749 |
| 中文摘要: |
| 作为轨道交通系统的核心子系统之一，对联锁系统进行形式化建模与分析，是保证其安全性的重要手段.形式化建模需要领域知识和形式化知识的结合，由于形式化知识难以掌握，领域专家在建模整个过程中都需要形式化专家的帮助.为了解决这个问题，针对联锁系统的故障随机性、行为实时性、构件可重用的特点，提出设计联锁领域特定语言IS-DSL描述具体的联锁系统的参数，并基于随机混成自动机模板自动生成联锁系统的形式化模型，以进一步在此基础上进行安全分析.首先对联锁系统模型进行分析，根据不同案例设计其领域特定语言；其次，确定联锁系统的系统模型模板，包括环境构件模板和控制器模板，并举例抽取其随机混成自动机模板；在模板基础上定义系统模型生成过程，让领域专家可以通过领域特定语言，输入参数自动生成具体的随机混成自动机系统模型；最后以某站联锁系统为例，展示了基于模板的具体系统模型的生成过程，并通过基于系统模型的事故预测分析，证明了该方法的可行性与有效性. |
| 英文摘要: |
| As a core subsystem of the rail transit systems, the formal modeling and analysis of the interlocking system is an important means to ensure its safety. Formalization requires both domain knowledge and formal knowledge. Since formal knowledge is difficult to master, domain experts need the help of formal experts throughout the modeling process. To solve this problem, aiming at the characteristics of fault randomness, real-time behavior, and reusability of components in railway interlocking systems, a specific language IS-DSL is proposed to describe the parameters of specific interlocking system. A formal model of interlocking system is generated automatically based on the stochastic hybrid automata (SHA) templates, to carry out further safety analysis. In this study, the model of interlocking system is analyzed firstly, and the domain specific language is designed according to different cases. Secondly, the templates of the interlocking system model, including environment component templates and controller template are established, and the SHA templates are extracted as examples. Based on these templates, the system model generation process is defined, so that the domain experts can automatically generate the specific SHA model by inputting parameters through the IS-DSL. Finally, the interlocking system of a station is taken as an example to show the generation process. The following accident prediction analysis based on this system model proves the feasibility and effectiveness of the proposed approach. |
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