Theoretical Analysis of GP-Evolved Risk Evaluation Formulas for Spectrum Based Fault Localisation
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @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