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An executable framework for modeling and validating cooperative capability requirements in emergency response system

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摘要 As the scale of current systems become larger and larger and their complexity is increasing gradually,research on executable models in the design phase becomes significantly important as it is helpful to simulate the execution process and capture defects of a system in advance.Meanwhile,the capability of a system becomes so important that stakeholders tend to emphasize their capability requirements when developing a system.To deal with the lack of official specifications and the fundamental theory basis for capability requirement,we propose a cooperative capability requirements(CCR)meta-model as a theory basis for researchers to refer to in this research domain,in which we provide detailed definition of the CCR concepts,associations and rules.Moreover,we also propose an executable framework,which may enable modelers to simulate the execution process of a system in advance and do well in filling the inconsistency and semantic gaps between stakeholders’requirements and their models.The primary working mechanism of the framework is to transform the Alf activity meta-model into the communicating sequential process(CSP)process meta-model based on some mapping rules,after which the internal communication mechanism between process nodes is designed to smooth the execution of behaviors in a CSP system.Moreover,a validation method is utilized to check the correctness and consistency of the models,and a self-fixing mechanism is used to fix the errors and warnings captured during the validation process automatically.Finally,a validation report is generated and fed back to the modelers for system optimization.
出处 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2021年第4期889-906,共18页 系统工程与电子技术(英文版)
基金 supported by the National Key R&D Program of China(2018YFC0806900) the China Postdoctoral Science Foundation Funded Project(2018M633757) the Primary Research&Development Plan of Jiangsu Province(BE2016904,BE2017616,BE2018754,BE2019762) Jiangsu Province Postdoctoral Science Foundation Funded Project(2019K185).
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