Scaling-up domain-specific modelling languages through modularity services

Abstract

Context: Model-driven engineering (MDE) promotes the active use of models in all phases of software development. Even though models are at a high level of abstraction, large or complex systems still require building monolithic models that prove to be too big for their processing by existing tools, and too difficult to comprehend by users. While modularization techniques are well-known in programming languages, they are not the norm in MDE. Objective: Our goal is to ease the modularization of models to allow their efficient processing by tools and facilitate their management by users. Method: We propose five patterns that can be used to extend a modelling language with services related to modularization and scalability. Specifically, the patterns allow defining model fragmentation strategies, scoping and visibility rules, model indexing services, and scoped constraints. Once the patterns have been applied to the meta-model of a modelling language, we synthesize a customized modelling environment enriched with the defined services, which become applicable to both existing monolithic legacy models and new models. Results: Our proposal is supported by a tool called EMF-Splitter, combined with the Hawk model indexer. Our experiments show that this tool improves the validation performance of large models. Moreover, the analysis of 224 meta-models from OMG standards, and a public repository with more than 300 meta-models, demonstrates the applicability of our patterns in practice. Conclusions: Modularity mechanisms typically employed in programming IDEs can be successfully transferred to MDE, leading to more scalable and structured domain-specific modelling languages and environments.

Publication DOI: https://doi.org/10.1016/j.infsof.2019.05.010
Divisions: College of Engineering & Physical Sciences > Computer Science
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
College of Engineering & Physical Sciences
Additional Information: © 2019, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ Funding: R&D programme of the Madrid Region (project FORTE, S2018/TCS-4314), and the Spanish Ministry of Science (project MASSIVE, RTI2018-095255-B-I00).
Uncontrolled Keywords: Domain-specific modelling languages,Meta-modelling,Model-driven engineering,Scalability,Software,Information Systems,Computer Science Applications
Full Text Link:
Related URLs: https://linking ... 950584919301259 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2019-11-01
Published Online Date: 2019-05-25
Accepted Date: 2019-05-25
Authors: Garmendia, Antonio
Guerra, Esther
de Lara, Juan
García-Domínguez, Antonio (ORCID Profile 0000-0002-4744-9150)
Kolovos, Dimitris

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