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abstract

Self-focusing genetic programming for software optimisation

Published:06 July 2013Publication History

ABSTRACT

Approaches in the area of Search Based Software Engineering (SBSE) have seen Genetic Programming (GP) algorithms applied to the optimisation of software. While the potential of GP for this task has been demonstrated, the complexity of real-world software code bases poses a scalability problem for its serious application. To address this scalability problem, we inspect a form of GP which incorporates a mechanism to focus operators to relevant locations within a program code base. When creating offspring individuals, we introduce operator node selection bias by allocating values to nodes within an individual. Offspring values are inherited and updated when a difference in behaviour between offspring and parent is found. We argue that this approach may scale to find optimal solutions in more complex code bases under further development.

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  1. Self-focusing genetic programming for software optimisation

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    • 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.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 6 July 2013

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