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The Role of Metamodeling in Systems Development

The Role of Metamodeling in Systems Development

Balsam A. J. Mustafa, Mazlina Abdul Majid
Copyright: © 2023 |Pages: 16
ISBN13: 9781799892205|ISBN10: 1799892204|EISBN13: 9781799892212
DOI: 10.4018/978-1-7998-9220-5.ch145
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MLA

Mustafa, Balsam A. J., and Mazlina Abdul Majid. "The Role of Metamodeling in Systems Development." Encyclopedia of Data Science and Machine Learning, edited by John Wang, IGI Global, 2023, pp. 2421-2436. https://doi.org/10.4018/978-1-7998-9220-5.ch145

APA

Mustafa, B. A. & Majid, M. A. (2023). The Role of Metamodeling in Systems Development. In J. Wang (Ed.), Encyclopedia of Data Science and Machine Learning (pp. 2421-2436). IGI Global. https://doi.org/10.4018/978-1-7998-9220-5.ch145

Chicago

Mustafa, Balsam A. J., and Mazlina Abdul Majid. "The Role of Metamodeling in Systems Development." In Encyclopedia of Data Science and Machine Learning, edited by John Wang, 2421-2436. Hershey, PA: IGI Global, 2023. https://doi.org/10.4018/978-1-7998-9220-5.ch145

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Abstract

Software systems developers are encountering different challenges as systems become increasingly complex due to numerous customers' needs that lead to a system with rich functionalities to be delivered within a short schedule. Developers also have to manage a variety of implementation methods, design techniques, and development processes. Researchers proposed “languages” as a solution to these problems. Meta-modeling is a method for defining the abstract syntax of a language. It makes the development of a language simpler allowing the designers to directly map the classes identified in domain analysis to classes in the meta-model. The meta-model expresses what models include such as concepts, relationships between them, and maybe the rules of how these concepts can be interrelated. This article presents an overview of the role and importance of meta-models in system development and their relationship with modeling languages. It highlights different aspects of metamodels standards, categories, and challenges in the research of meta-modeling.

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