Using Genetic Improvement and Code Transplants to Specialise a C++ Program to a Problem Class

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Petke:2014:EuroGP,
  author =       "Justyna Petke and Mark Harman and 
                 William B. Langdon and Westley Weimer",
  title =        "Using Genetic Improvement and Code Transplants to
                 Specialise a {C++} Program to a Problem Class",
  booktitle =    "17th European Conference on Genetic Programming",
  editor =       "Miguel Nicolau and Krzysztof Krawiec and 
                 Malcolm I. Heywood and Mauro Castelli and Pablo Garcia-Sanchez and 
                 Juan J. Merelo and Victor M. {Rivas Santos} and 
                 Kevin Sim",
  year =         "2014",
  series =       "LNCS",
  volume =       "8599",
  publisher =    "Springer",
  pages =        "137--149",
  address =      "Granada, Spain",
  month =        "23-25 " # apr,
  organisation = "EvoStar",
  keywords =     "genetic algorithms, genetic programming, evolutionary
                 programming, SBSE, software enngineering, genetic
                 improvement, code transplants, code specialisation",
  isbn13 =       "978-3-662-44302-6",
  URL =          "http://www0.cs.ucl.ac.uk/staff/J.Petke/papers/Petke_2014_EuroGP.pdf",
  DOI =          "doi:10.1007/978-3-662-44303-3_12",
  size =         "12 pages",
  abstract =     "Genetic Improvement (GI) is a form of Genetic
                 Programming that improves an existing program. We use
                 GI to evolve a faster version of a C++ program, a
                 Boolean satisfiability (SAT) solver called MiniSAT,
                 specialising it for a particular problem class, namely
                 Combinatorial Interaction Testing (CIT), using
                 automated code transplantation. Our GI-evolved solver
                 achieves overall 17percent improvement, making it
                 comparable with average expert human performance.
                 Additionally, this automatically evolved solver is
                 faster than any of the human-improved solvers for the
                 CIT problem.",
  notes =        "GI system available from Justyna Petke via
                 e-mail

                 Slides at
                 http://www.cs.ucl.ac.uk/staff/W.Langdon/gismo/petke_2014_eurogp_slides.pdf

                 Winner of Silver at 11th Annual HUMIES Awards 2014
                 Vancouver, British Columbia, see
                 \cite{Petke:2014:humie}. Extended by
                 \cite{Petke:2017:ieeeTSE}.

                 Part of \cite{Nicolau:2014:GP} EuroGP'2014 held in
                 conjunction with EvoCOP2014, EvoBIO2014, EvoMusArt2014
                 and EvoApplications2014",
}

Genetic Programming entries for Justyna Petke Mark Harman William B Langdon Westley Weimer

Citations