Genetic Programming meets Model-Driven Development

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  author =       "Thomas Weise and Michael Zapf and 
                 Mohammad Ullah Khan and Kurt Geihs",
  title =        "Genetic Programming meets Model-Driven Development",
  booktitle =    "7th International Conference on Hybrid Intelligent
                 Systems, HIS 2007",
  year =         "2007",
  language =     "en",
  editor =       "Andreas K{\"o}nig and Mario K{\"o}ppen and 
                 Ajith Abraham and Christian Igel and Nikola Kasabov",
  pages =        "332--335",
  address =      "Kaiserslautern, Germany",
  month =        "17-19 " # sep,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming, SBSE, GP,
                 Model Driven Development, MDD, Model Driven
                 Architecture, MDA, XMI, MOF-Skript, UML, Distributed
                 Algorithms, SBSE",
  isbn13 =       "978-0-7695-2946-2",
  URL =          "",
  DOI =          "doi:10.1109/ICHIS.2007.4344073",
  DOI =          "doi:10.1109/HIS.2007.11",
  abstract =     "Genetic programming is known to provide good solutions
                 for many problems like the evolution of network
                 protocols and distributed algorithms. In such cases it
                 is most likely a hardwired module of a design framework
                 that assists the engineer to optimise specific aspects
                 of the system to be developed. It provides its results
                 in a fixed format through an internal interface. In
                 this paper we show how the usefulness of genetic
                 programming can be increased remarkably by isolating it
                 as a component and integrating it into the model-driven
                 software development process. Our genetic programming
                 framework produces XMI-encoded UML models that can
                 easily be loaded into widely available modelling tools
                 which in turn posses code generation as well as
                 additional analysis and test capabilities. We use the
                 evolution of a distributed election algorithm as an
                 example to illustrate how genetic programming can be
                 combined with model-driven development. This example
                 clearly illustrates the advantages of our approach -
                 the generation of source code in different programming
  contents =     "* Introduction\\* Genetic Programming and MDD\\-
                 Model-Driven Development\\- Combining MDD and GP\\*
                 Evolving Distributed Algorithms\\- Evolving an Election
                 Algorithm\\* Creating a PIM\\- Control Flow Model\\-
                 Data Model\\- Modeling the Primitive Operations\\*
                 Transforming the UML Models\\* Conclusion",
  notes =        "also known as \cite{WZKG2007DGPFg}

                 Library of Congress Number 2007936727, Product Number
                 E2946. see

                 Longer version of \cite{WZKG2007DGPFd}. AST, PIM PSM,
                 multi-objective GP MOGP, MOFScript modelware, eclipse
                 modeling framework, C, Java.",

Genetic Programming entries for Thomas Weise Michael Zapf Mohammad Ullah Khan Kurt Geihs