Domain Specific MetaModeling for Deep Semantic Composability
Author(s) -
Zhi Zhu,
Yonglin Lei,
Abdurrahman Alshareef,
Hessam Sarjoughian,
Yifan Zhu
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2822661
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Current simulation models are not only represented in the form of traditional data or formula for pure theory analysis but expanded to be simulation modeling assets that are featured with complicated structure, diverse behaviors, and abundant semantics. Semantic composability, therefore, receives a constantly growing attention in recent years. So far, one of the popular solutions to enhance semantic expressiveness is domain specific modeling based on general metamodeling (GMM) facilities. But for some particular domains, researchers identified the need of deeper semantic expressiveness therefore proposed domain specific metamodeling (DSMM). Hence, this paper aims to explore the underlying methodologies of DSMM for supporting deep semantic composability. Compared with several usual alternatives based on GMM, this paper applies the multi-level metamodeling architecture to create a set of metamodeling primitives using an example named SEvent. In fact, SEvent is a novel formalism that slightly extends Petri net to support continuous states transition and continuous event triggering. As a proof of concept, we concentrate on developing the textual syntax of SEvent and using it to represent torpedo's behaviors.
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