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Scalable Models Using Model Transformation
Thomas Huining Feng, Edward A. Lee

Citation
Thomas Huining Feng, Edward A. Lee. "Scalable Models Using Model Transformation". 1st International Workshop on Model Based Architecting and Construction of Embedded Systems (ACESMB), September, 2008; Presentation may be found at http://chess.eecs.berkeley.edu/pubs/489.html.

Abstract
Higher-order model composition can be employed as a mechanism for scalable model construction. By creating a description that manipulates model fragments as first-class objects, designers' work of model creation and maintenance can be greatly simplified. In this paper, we present our approach to higher-order model composition based on model transformation. We define basic transformation rules to operate on the graph structures of actor models. The composition of basic transformation rules with heterogeneous models of computation form complex transformation systems, which we use to construct large models. We argue that our approach is more visual than the traditional approaches using textual model descriptions. It also has the advantage of allowing to dynamically modify models and to execute them on the fly. Our arguments are supported by a concrete example of constructing a distributed model of arbitrary size.

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Citation formats  
  • HTML
    Thomas Huining Feng, Edward A. Lee. <a
    href="http://chess.eecs.berkeley.edu/pubs/487.html">Scalable
    Models Using Model Transformation</a>, 1st
    International Workshop on Model Based Architecting and
    Construction of Embedded Systems (ACESMB), September, 2008;
    Presentation may be found at <a
    href="http://chess.eecs.berkeley.edu/pubs/489.html"
    >http://chess.eecs.berkeley.edu/pubs/489.html</a>.
  • Plain text
    Thomas Huining Feng, Edward A. Lee. "Scalable Models
    Using Model Transformation". 1st International Workshop
    on Model Based Architecting and Construction of Embedded
    Systems (ACESMB), September, 2008; Presentation may be found
    at <a
    href="http://chess.eecs.berkeley.edu/pubs/489.html"
    >http://chess.eecs.berkeley.edu/pubs/489.html</a>.
  • BibTeX
    @inproceedings{FengLee08_ScalableModelsUsingModelTransformation,
        author = {Thomas Huining Feng and Edward A. Lee},
        title = {Scalable Models Using Model Transformation},
        booktitle = {1st International Workshop on Model Based
                  Architecting and Construction of Embedded Systems
                  (ACESMB)},
        month = {September},
        year = {2008},
        note = {Presentation may be found at <a
                  href="http://chess.eecs.berkeley.edu/pubs/489.html"
                  >http://chess.eecs.berkeley.edu/pubs/489.html</a>.},
        abstract = {Higher-order model composition can be employed as
                  a mechanism for scalable model construction. By
                  creating a description that manipulates model
                  fragments as first-class objects, designers' work
                  of model creation and maintenance can be greatly
                  simplified. In this paper, we present our approach
                  to higher-order model composition based on model
                  transformation. We define basic transformation
                  rules to operate on the graph structures of actor
                  models. The composition of basic transformation
                  rules with heterogeneous models of computation
                  form complex transformation systems, which we use
                  to construct large models. We argue that our
                  approach is more visual than the traditional
                  approaches using textual model descriptions. It
                  also has the advantage of allowing to dynamically
                  modify models and to execute them on the fly. Our
                  arguments are supported by a concrete example of
                  constructing a distributed model of arbitrary size.},
        URL = {http://chess.eecs.berkeley.edu/pubs/487.html}
    }
    

Posted by Thomas Huining Feng on 20 Sep 2008.
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