Exploring Fitness and Edit Distance of Mutated Python Programs

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Haraldsson:2017:EuroGP,
  author =       "Saemundur O. Haraldsson and John R. Woodward and 
                 Alexander E. I. Brownlee and David Cairns",
  title =        "Exploring Fitness and Edit Distance of Mutated Python
                 Programs",
  booktitle =    "EuroGP 2017: Proceedings of the 20th European
                 Conference on Genetic Programming",
  year =         "2017",
  month =        "19-21 " # apr,
  editor =       "Mauro Castelli and James McDermott and 
                 Lukas Sekanina",
  series =       "LNCS",
  volume =       "10196",
  publisher =    "Springer Verlag",
  address =      "Amsterdam",
  pages =        "19--34",
  organisation = "species",
  keywords =     "genetic algorithms, genetic programming, Genetic
                 Improvement",
  DOI =          "doi:10.1007/978-3-319-55696-3_2",
  abstract =     "Genetic Improvement (GI) is the process of using
                 computational search techniques to improve existing
                 software e.g. in terms of execution time, power
                 consumption or correctness. As in most heuristic search
                 algorithms, the search is guided by fitness with GI
                 searching the space of program variants of the original
                 software. The relationship between the program space
                 and fitness is seldom simple and often quite difficult
                 to analyse. This paper makes a preliminary analysis of
                 GI's fitness distance measure on program repair with
                 three small Python programs. Each program undergoes
                 incremental mutations while the change in fitness as
                 measured by proportion of tests passed is monitored. We
                 conclude that the fitnesses of these programs often
                 does not change with single mutations and we also
                 confirm the inherent discreteness of bug fixing fitness
                 functions. Although our findings cannot be assumed to
                 be general for other software they provide us with
                 interesting directions for further investigation.",
  notes =        "Part of \cite{Castelli:2017:GP} EuroGP'2017 held in
                 conjunction with EvoCOP2017, EvoMusArt2017 and
                 EvoApplications2017",
}

Genetic Programming entries for Saemundur Oskar Haraldsson John R Woodward Alexander E I Brownlee David Cairns

Citations