{"title":"跨开发和事件图形式化的模型转换","authors":"Neal DeBuhr, H. Sarjoughian","doi":"10.1109/WSC52266.2021.9715356","DOIUrl":null,"url":null,"abstract":"This paper develops a model transformation mechanism across the Discrete Event System Specification (DEVS) and Event Graph (EG) modeling formalisms. We detail this cross-formalism model transformation from methodological and software implementation perspectives. By using simple, well-defined, and automated mechanisms of cross-formalism model transformation, modelers establish a plurality of vantage points, from which to understand and communicate model behavior. Model characteristics may be clarified, emphasized, obfuscated, or hidden across these different vantage points. This paper, therefore, serves as a step toward research into better modeling that can improve soft factors such as model reasoning and collaborative model design for developing better simulations.","PeriodicalId":369368,"journal":{"name":"2021 Winter Simulation Conference (WSC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Model Transformation Across Devs and Event Graph Formalisms\",\"authors\":\"Neal DeBuhr, H. Sarjoughian\",\"doi\":\"10.1109/WSC52266.2021.9715356\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper develops a model transformation mechanism across the Discrete Event System Specification (DEVS) and Event Graph (EG) modeling formalisms. We detail this cross-formalism model transformation from methodological and software implementation perspectives. By using simple, well-defined, and automated mechanisms of cross-formalism model transformation, modelers establish a plurality of vantage points, from which to understand and communicate model behavior. Model characteristics may be clarified, emphasized, obfuscated, or hidden across these different vantage points. This paper, therefore, serves as a step toward research into better modeling that can improve soft factors such as model reasoning and collaborative model design for developing better simulations.\",\"PeriodicalId\":369368,\"journal\":{\"name\":\"2021 Winter Simulation Conference (WSC)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 Winter Simulation Conference (WSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WSC52266.2021.9715356\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Winter Simulation Conference (WSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WSC52266.2021.9715356","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Model Transformation Across Devs and Event Graph Formalisms
This paper develops a model transformation mechanism across the Discrete Event System Specification (DEVS) and Event Graph (EG) modeling formalisms. We detail this cross-formalism model transformation from methodological and software implementation perspectives. By using simple, well-defined, and automated mechanisms of cross-formalism model transformation, modelers establish a plurality of vantage points, from which to understand and communicate model behavior. Model characteristics may be clarified, emphasized, obfuscated, or hidden across these different vantage points. This paper, therefore, serves as a step toward research into better modeling that can improve soft factors such as model reasoning and collaborative model design for developing better simulations.