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Models and Metamodels for Systems Specification

This document presents a comprehensive examination of models and metamodels for system specification, detailing the classification of systems into various types, including untimed, timed, static, dynamic, deterministic, and probabilistic systems. It explores model composition, parallelism, and requirements for effective system modeling. Key case studies include telecom systems and a variety of applications such as audio processing, elevator control, and algorithmic processes. This work aims to reduce modeling complexity while enhancing understanding of heterogeneous systems through appropriate models and interoperability.

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Models and Metamodels for Systems Specification

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  1. Programa de Pós-Graduação em Ciência da Computação Models and Metamodels for Systems Specification César Augusto Missio Marcon

  2. Type of Systems System Untimed Timed Static Dynamic Asynchronous Synchronous Continuous Discrete Deterministic Non-deterministic Totally ordered Partially ordered unordered Probabilistic • A spring operation • A continuous system for clothes washing • An internal panel of an elevator • An algorithm for factorial calculus • People leaving a football stadium • An audio processing system. This one gets a regular input signal and emits a signal after a delay D. The output audio is of type PCM

  3. Model Composition • Parallelism • Two kinds of parallelism • Transmitter and Receiver, normally operate independently and in parallel • The information exchange between upper and lower protocol layers • Modeling Requirements A need to express intrinsic features or to describe behaviors often found in systems • Parallelism • Modularity • Hierarchy • Communicability • Dynamicity • Statebility • Determinism • Real time operation (NRTS, CRTS, NCRTS) • Exception • Reliability

  4. Model Composition E.g. statebility requirement  the need of a system being represented by states • Modeling Primitives An element that fulfill requirements and is capable to satisfying the needs of systems modeling

  5. Composition of MoCs • Models of Computation • Provides a formal structure for modeling a significant amount of computational systems classes • Single MOCs: created by primitives • Composite MOCs: created by single MOCs composition or specialization

  6. A Metamodel Metamodel is used in the understanding of the systems modeling

  7. A Metamodel • Heterogeneous System Modeling with Homogeneous Subsystem Modeling Approach • Objective • Reduce the modeling complexity • Target Systems • Heterogeneous systems with many subsystems • Tasks • Choose models for each subsystem • Choose interoperability models (main drawback)

  8. Telecom Systems Case Study Class 1: Low level protocol systems (e.g. SDH and E1) Telecom systems can be weakly defined as those systems responsible for information exchange • Classification Criteria

  9. Telecom Systems Case Study

  10. Telecom Systems Case Study

  11. Programa de Pós-Graduação em Ciência da Computação Models and Metamodels for Systems Specification César Augusto Missio Marcon

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