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Compositional Predictability Analysis of Mixed Critical Real Time Systems

  • Abdeldjalil Boudjadar
  • Juergen Dingel
  • Boris Madzar
  • Jin Hyun Kim
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 596)

Abstract

This paper introduces a compositional framework for analyzing the predictability of component-based embedded real-time systems. The framework utilizes automated analysis of tasks and communication architdepicts the structureectures to provide insight on the schedulability and data flow. The communicating tasks are gathered within components, making the system architecture hierarchical. The system model is given by a set of Parameterized Stopwatch Automata modeling the behavior and dependency of tasks, while we use Uppaal to analyze the predictability. Thanks to the Uppaal language, our model-based framework allows expressive modeling of the behavior. Moreover, our reconfigurable framework is customizable and scalable due to the compositional analysis. The analysis time and cost benefits of our framework are discussed through an avionic case study.

Keywords

Task Execution Dependency Relation Predictability Analysis Dependent Task Brake Pressure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Abdeldjalil Boudjadar
    • 1
  • Juergen Dingel
    • 2
  • Boris Madzar
    • 2
  • Jin Hyun Kim
    • 3
  1. 1.Linköping UniversityLinköpingSweden
  2. 2.Queen’s UniversityKingstonCanada
  3. 3.INRIARennesFrance

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