Making Better Use of Repair Templates in Automated Program Repair: A Multi-Objective Approach
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InCollection{Yuan:2020:beacon,
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author = "Yuan Yuan and Wolfgang Banzhaf",
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title = "Making Better Use of Repair Templates in Automated
Program Repair: A Multi-Objective Approach",
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booktitle = "Evolution in Action: Past, Present and Future: A
Festschrift in Honor of Erik D. Goodman",
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publisher = "Springer",
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year = "2020",
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editor = "Wolfgang Banzhaf and Betty H. C. Cheng and
Kalyanmoy Deb and Kay E. Holekamp and Richard E. Lenski and
Charles Ofria and Robert T. Pennock and
William F. Punch and Danielle J. Whittaker",
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series = "Genetic and Evolutionary Computation book series",
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chapter = "26",
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pages = "385--407",
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keywords = "genetic algorithms, genetic programming, genetic
improvement, APR, Program repair, evolutionary
multi-objective optimisation, repair templates",
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isbn13 = "978-3-030-39833-0",
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DOI = "doi:10.1007/978-3-030-39831-6_26",
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abstract = "The automation of program repair can be coached in
terms of search algorithms. Repair templates derived
from common bug-fix patterns can be used to determine a
promising search space with potentially many correct
patches, a space that can be effectively explored by GP
methods. Here we propose a new repair system, ARJA-p,
extended from our earlier ARJA system of bug repair for
JAVA, which integrates and enhances the performance of
the first approach that combines repair templates and
EC, PAR. Empirical results on 224 real bugs in
Defects4J show that ARJA-p outperforms state-of-the-art
repair approaches by a large margin, both in terms of
the number of bugs fixed and of their correctness.
Specifically, ARJA-p can increase the number of fixed
bugs in Defects4J by 29.2percent (from 65 to 84) and
the number of correctly fixed bugs by 42.3percent (from
26 to 37).",
- }
Genetic Programming entries for
Yuan Yuan
Wolfgang Banzhaf
Citations