Language family engineering with product lines of multi-level models
| Autor: | Juan de Lara, Esther Guerra |
|---|---|
| Přispěvatelé: | UAM. Departamento de Ingeniería Informática |
| Rok vydání: | 2021 |
| Předmět: |
Informática
Correctness Computer science Programming language Theory Open set Software language engineering Reuse computer.software_genre Theoretical Computer Science Language primitive MetaDepth Product (mathematics) Multi-level modelling Theory of computation Product lines Language family Meta-modelling computer Domain-specific languages Software |
| Zdroj: | Biblos-e Archivo. Repositorio Institucional de la UAM instname |
| Popis: | Modelling is an essential activity in software engineering. Ittypically involves two meta-levels: one includes meta-models thatdescribe modelling languages, and the other contains models built byinstantiating those meta-models. Multi-level modelling generalizes this approach by allowing models to span an arbitrarynumber of meta-levels. A scenario that profits from multi-levelmodelling is the definition of language families that can bespecialized (e.g., for different domains) by successive refinementsat subsequent meta-levels, hence promoting language reuse. Thisenables an open set of variability options given by allpossible specializations of the language family. However,multi-level modelling lacks the ability to express closed variability regarding the availability of language primitives or thepossibility to opt between alternative primitive realizations. Thislimits the reuse opportunities of a language family. To improve thissituation, we propose a novel combination of product lines withmulti-level modelling to cover both open and closed variability. Ourproposal is backed by a formal theory that guarantees correctness,enables top-down and bottom-up language variability design, and isimplemented atop the MetaDepth multi-level modelling tool This work has been funded by the SpanishMinistry of Science (project MASSIVE, RTI2018-095255- B-I00), by the R&D programme of Madrid (project FORTE, P2018/TCS-4314), and the Universidad Autónoma de Madrid |
| Databáze: | OpenAIRE |
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