skip to main content
10.1145/2464576.2480790acmconferencesArticle/Chapter ViewAbstractPublication PagesgeccoConference Proceedingsconference-collections
abstract

Exploring automated software composition with genetic programming

Published:06 July 2013Publication History

ABSTRACT

Much research has been performed in investigating the numerous dimensions of software composition. Challenges include creating a composition-based design process, designing software for reuse, investigating various strategies for composition, and automating the composition process. Depending on the complexity of the relevant components, numerous composition strategies may exist, each of which may have several options and variations for aggregate steps in realizing these strategies. This paper presents an evolutionary computation-based framework for automatically searching for and realizing an optimal composition strategy for composing a given target module into an existing software system.

References

  1. S. Apel, C. Kastner, and C. Lengauer. Featurehouse: Language-independent, automated software composition. In Software Engineering, 2009. ICSE 2009. IEEE 31st International Conf. on, pages 221--231, Vancouver, BC, Canada, 2009. IEEE. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. N. L. Cramer. A representation for the adaptive generation of simple sequential programs. In Proceedings of an International Conf. on Genetic Algorithms and the Applications, pages 183--187, Pittsburgh, PA, USA, 1985. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. C. Gagné and M. Parizeau. Open beagle: A new versatile c framework for evolutionary computation. In Proceedings of GECCO, New York, NY, USA, 2002.Google ScholarGoogle Scholar
  4. J. H. Holland. Adaptation in Natural and Artificial Systems. MIT Press, Cambridge, MA, USA, 1992. Google ScholarGoogle ScholarCross RefCross Ref
  5. J. R. Koza. Genetic programming as a means for programming computers by natural selection. Statistics and Computing, 4(2):87--112, 1994.Google ScholarGoogle ScholarCross RefCross Ref
  6. K.-K. Lau and T. Rana. A taxonomy of software composition mechanisms. Proc. 36th EUROMICRO SEAA, pages 102--110, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. T. Perkis. Stack-based genetic programming. In Evolutionary Computation, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the First IEEE Conf. on, pages 148--153. IEEE, 1994.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Exploring automated software composition with genetic programming

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Conferences
        GECCO '13 Companion: Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
        July 2013
        1798 pages
        ISBN:9781450319645
        DOI:10.1145/2464576
        • Editor:
        • Christian Blum,
        • General Chair:
        • Enrique Alba

        Copyright © 2013 Copyright is held by the owner/author(s)

        Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 6 July 2013

        Check for updates

        Qualifiers

        • abstract

        Acceptance Rates

        Overall Acceptance Rate1,669of4,410submissions,38%

        Upcoming Conference

        GECCO '24
        Genetic and Evolutionary Computation Conference
        July 14 - 18, 2024
        Melbourne , VIC , Australia

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader