Theoretical Analysis of GP-Evolved Risk Evaluation Formulas for Spectrum Based Fault Localisation

Created by W.Langdon from gp-bibliography.bib Revision:1.3949

@TechReport{Xie:2013fk,
  author =       "Xiaoyuan Xie and Fei-Ching Kuo and Tsong Yueh Chen and 
                 Shin Yoo and Mark Harman",
  title =        "Theoretical Analysis of GP-Evolved Risk Evaluation
                 Formulas for Spectrum Based Fault Localisation",
  institution =  "Department of Computer Science, University College
                 London",
  year =         "2013",
  type =         "Research Note",
  number =       "RN/13/06",
  address =      "Gower Street, London WC1E 6BT, UK",
  month =        "28 " # feb,
  keywords =     "genetic algorithms, genetic programming, SBSE, SBFL",
  URL =          "http://www.cs.ucl.ac.uk/fileadmin/UCL-CS/research/rn-13-06__2_.pdf",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.378.9601",
  size =         "11 pages",
  abstract =     "Risk evaluation formulae convert program spectrum data
                 from test executions into suspiciousness score,
                 according to which statements are ranked to aid
                 debugging activities. Designing such formulas remained
                 largely a manual task until Genetic Programming has
                 been recently applied: resulting formulae showed
                 promising performance in empirical evaluation. We
                 investigate the GP-evolved formulae theoretically and
                 prove that GP has produced four maximal formulae that
                 had not been known before. More interestingly, some of
                 the newly found maximal formulae show characteristics
                 that may seem inconsistent with human intuition. This
                 is the first SBSE result with provable human
                 competitiveness.",
  notes =        "See also \cite{Xie:2013:SSBSE}",
}

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

Citations