Human Competitiveness of Genetic Programming in Spectrum Based Fault Localisation: Theoretical and Empirical Analysis

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@Article{Yoo:TOSEM:sbfl,
  author =       "Shin Yoo and Xiaoyuan Xie and Fei-Ching Kuo and 
                 Tsong Yueh Chen and Mark Harman",
  title =        "Human Competitiveness of Genetic Programming in
                 Spectrum Based Fault Localisation: Theoretical and
                 Empirical Analysis",
  journal =      "ACM Transactions on Software Engineering and
                 Methodology",
  year =         "2017",
  volume =       "26",
  number =       "1",
  pages =        "4:1--4:30",
  month =        jul,
  note =         "Winner Silver Humie 2017",
  keywords =     "genetic algorithms, genetic programming, SBSE,
                 Spectrum Based Fault Localisation",
  ISSN =         "1049-331X",
  URL =          "http://www.human-competitive.org/sites/default/files/yoo-paper.pdf",
  URL =          "http://www.human-competitive.org/sites/default/files/yoo-text_0.txt",
  DOI =          "doi:10.1145/3078840",
  acmid =        "3078840",
  size =         "31 pages",
  abstract =     "We report on the application of Genetic Programming to
                 Software Fault Localisation, a problem in the area of
                 Search Based Software Engineering (SBSE). We give both
                 empirical and theoretical evidence for the human
                 competitiveness of the evolved fault localisation
                 formulae under the single fault scenario, compared to
                 those generated by human ingenuity and reported in many
                 papers, published over more than a decade. Though there
                 have been previous human competitive results claimed
                 for SBSE problems, this is the first time that evolved
                 solutions have been formally proved to be human
                 competitive. We further prove that no future human
                 investigation could outperform the evolved solutions.
                 We complement these proofs with an empirical analysis
                 of both human and evolved solutions, which indicates
                 that the evolved solutions are not only theoretically
                 human competitive, but also convey similar practical
                 benefits to human-evolved counterparts.",
  notes =        "Entered 2017 Humies
                 http://www.human-competitive.org/awards",
}

Genetic Programming entries for Shin Yoo XiaoYuan Xie Fei-Ching (Diana) Kuo Tsong Yueh Chen Mark Harman

Citations