SESep 15, 2015

Integration of Heterogeneous Modeling Languages via Extensible and Composable Language Components

arXiv:1509.04502v146 citations
Originality Incremental advance
AI Analysis

This addresses the challenge of onerous and context-specific language integration for software engineers, though it appears incremental as it builds on existing language workbench concepts.

The paper tackles the problem of integrating heterogeneous modeling languages in model-driven engineering by introducing a method for engineering grammar-based language components that are syntactically composable and reusable, resulting in a systematic and efficient syntax-oriented composition approach.

Effective model-driven engineering of complex systems requires to appropriately describe different specific system aspects. To this end, efficient integration of different heterogeneous modeling languages is essential. Modeling language integaration is onerous and requires in-depth conceptual and technical knowledge and ef- fort. Traditional modeling lanugage integration approches require language engineers to compose monolithic language aggregates for a specific task or project. Adapting these aggregates cannot be to different contexts requires vast effort and makes these hardly reusable. This contribution presents a method for the engineering of grammar-based language components that can be independently developed, are syntactically composable, and ultimately reusable. To this end, it introduces the concepts of language aggregation, language embed- ding, and language inheritance, as well as their realization in the language workbench MontiCore. The result is a generalizable, systematic, and efficient syntax-oriented composition of languages that allows the agile employment of modeling languages efficiently tailored for individual software projects.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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