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Open Access 2024 | OriginalPaper | Buchkapitel

Model-Driven Engineering of Microservice Architectures—The LEMMA Approach

verfasst von : Florian Rademacher, Philip Wizenty, Jonas Sorgalla, Sabine Sachweh, Albert Zündorf

Erschienen in: Ernst Denert Award for Software Engineering 2022

Verlag: Springer Nature Switzerland

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This chapter presents LEMMA (Language Ecosystem for Modeling Microservice Architecture). LEMMA enables the application of Model-Driven Engineering (MDE) to Microservice Architecture (MSA). LEMMA mitigates the complexity of MSA by decomposing it along four viewpoints on microservice architectures, each capturing the concerns of different MSA stakeholders in dedicated architecture models. LEMMA formalizes the syntax and semantics of these models with specialized modeling languages that are integrated based on an import mechanism, thus enabling holistic MSA modeling. LEMMA also bundles its own model processing framework (MPF) to facilitate model processor implementation for technology-savvy MSA stakeholders without a background in MDE.We describe the design and development of LEMMA and exemplify the usage of its modeling languages and MPF for a case study microservice architecture. In addition, we present practical applications of LEMMA for microservice code generation, architecture reconstruction, quality analysis, defect resolution, and establishing a common architecture understanding. A comparison of LEMMA with related approaches reveals that LEMMA has particular strengths in (i) language-level extensibility, allowing model-based reification of architectural patterns; (ii) model processing, by bundling sophisticated code generators and static quality analyzers; and (iii) versatility, making LEMMA applicable in microservice development, operation, architecture reconstruction, and quality assessment.

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Metadaten
Titel
Model-Driven Engineering of Microservice Architectures—The LEMMA Approach
verfasst von
Florian Rademacher
Philip Wizenty
Jonas Sorgalla
Sabine Sachweh
Albert Zündorf
Copyright-Jahr
2024
DOI
https://doi.org/10.1007/978-3-031-44412-8_5

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