Case Study: Model Transformations for Time-triggered Languages | Zendy

Tivadar Szemethy | Zendy

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Case Study: Model Transformations for Time-triggered Languages

Author(s) -

Tivadar Szemethy

Publication year - 2006

Publication title -

electronic notes in theoretical computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.242

H-Index - 60

ISSN - 1571-0661

DOI - 10.1016/j.entcs.2005.10.024

Subject(s) - graph rewriting , computer science , model transformation , correctness , transformation (genetics) , programming language , unified modeling language , theoretical computer science , graph , rewriting , automaton , code generation , algorithm , artificial intelligence , software , biochemistry , chemistry , consistency (knowledge bases) , computer security , key (lock) , gene

In this study, we introduce a model transformation tool for a time-triggered language: Giotto. The tool uses graphs to represent the source code (Giotto) and the target (the schedule-carrying code) of the transformation, and has been implemented entirely using graph rewriting techniques. The meta-models of the input and the output were specified using standard (UML) technology, and the transformation itself as a programmed graph rewriting system (in GReAT). The approach illustrates how a non-trivial model transformation can be implemented using graph transformations, and how the results obtained here could be used for the formal verification of embedded systems models. The transformation developed here forms the first step towards translating high-level, domain-specific models (that use concepts of the time-triggered language) into analysis models (that use concepts from the language of the analysis, e.g. timed automata). Using a formal approach such as graph transformation helps ensure the correctness of this transformation process

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