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Rule-Based Modeling and Static Analysis of Self-adaptive Systems by Graph Transformation

  • Antonio Bucchiarone
  • Hartmut Ehrig
  • Claudia Ermel
  • Patrizio Pelliccione
  • Olga Runge
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8950)

Abstract

Software systems nowadays require continuous operation despite changes both in user needs and in their operational environments. Self-adaptive systems are typically instrumented with tools to autonomously perform adaptation to these changes while maintaining some desired properties. In this paper we model and analyze self-adaptive systems by means of typed, attributed graph grammars. The interplay of different grammars representing the application and the adaptation logic is realized by an adaption manager. Within this formal framework we define consistency and operational properties that are maintained despite adaptations and we give static conditions for their verification. The overall approach is supported by the AGG tool for modeling, simulating, and analyzing graph transformation systems. A case study modeling a business process that adapts to changing environment conditions is used to demonstrate and validate the formal framework.

Keywords

Business Process Graph Transformation Composite Service Normal Rule Type Graph 
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 2015

Authors and Affiliations

  • Antonio Bucchiarone
    • 1
  • Hartmut Ehrig
    • 2
  • Claudia Ermel
    • 2
  • Patrizio Pelliccione
    • 3
  • Olga Runge
    • 2
  1. 1.Fondazione Bruno KesslerTrentoItaly
  2. 2.Technische Universität BerlinGermany
  3. 3.Chalmers University of Technology and University of GothenburgSweden

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