SEDBSep 29, 2020

Modelling service-oriented systems and cloud services with Heraklit

arXiv:2009.14040v116 citations
Originality Synthesis-oriented
AI Analysis

This addresses the difficulty in systematically composing and representing digital infrastructures for modelers, though it appears incremental as it builds on existing concepts.

The paper tackles the challenge of modeling and analyzing complex service-oriented systems and cloud services by introducing Heraklit, a framework that integrates composition, hierarchies, data structures, and behavior descriptions, providing a foundation for Systems Mining.

Modern and next generation digital infrastructures are technically based on service oriented structures, cloud services, and other architectures that compose large systems from smaller subsystems. The composition of subsystems is particularly challenging, as the subsystems themselves may be represented in different languages, modelling methods, etc. It is quite challenging to precisely conceive, understand, and represent this kind of technology, in particular for a given level of abstraction. To capture refinement and abstraction principles, various forms of "technology stacks" and other semi-formal or natural language based on presentations have been suggested. Generally, useful concepts to compose such systems in a systematic way are even more rare. Heraklit provides means, principles, and unifying techniques to model and to analyze digital infrastructures. Heraklit integrates composition and hierarchies of subsystems, concrete and abstract data structures, as well as descriptions of behaviour. A distinguished set of means supports the modeler to express their ideas. The modeller is free to choose the level of abstraction, as well as the kind of composition. Heraklit integrates new concepts with tried and tested ones. Such a framework provides the foundation for a comprehensive Systems Mining as the next step after Process Mining.

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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