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

Created by W.Langdon from gp-bibliography.bib Revision:1.8010

@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