A genetic programming approach to automated software repair

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  author =       "Stephanie Forrest and ThanhVu Nguyen and 
                 Westley Weimer and Claire {Le Goues}",
  title =        "A genetic programming approach to automated software
  booktitle =    "GECCO '09: Proceedings of the 11th Annual conference
                 on Genetic and evolutionary computation",
  year =         "2009",
  editor =       "Guenther Raidl and Franz Rothlauf and 
                 Giovanni Squillero and Rolf Drechsler and Thomas Stuetzle and 
                 Mauro Birattari and Clare Bates Congdon and 
                 Martin Middendorf and Christian Blum and Carlos Cotta and 
                 Peter Bosman and Joern Grahl and Joshua Knowles and 
                 David Corne and Hans-Georg Beyer and Ken Stanley and 
                 Julian F. Miller and Jano {van Hemert} and 
                 Tom Lenaerts and Marc Ebner and Jaume Bacardit and 
                 Michael O'Neill and Massimiliano {Di Penta} and Benjamin Doerr and 
                 Thomas Jansen and Riccardo Poli and Enrique Alba",
  pages =        "947--954",
  address =      "Montreal",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  month =        "8-12 " # jul,
  organisation = "SigEvo",
  note =         "Best paper",
  keywords =     "genetic algorithms, genetic programming, Software
                 Engineering, Testing and Debugging, Programming
                 Languages, Syntax, Algorithms, Software repair,
                 software engineering",
  isbn13 =       "978-1-60558-325-9",
  bibsource =    "DBLP, http://dblp.uni-trier.de",
  bibsource =    "OAI-PMH server at citeseerx.ist.psu.edu",
  DOI =          "doi:10.1145/1569901.1570031",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=",
  URL =          "http://www.cs.virginia.edu/~weimer/p/weimer-gecco2009.pdf",
  language =     "en",
  oai =          "oai:CiteSeerXPSU:",
  abstract =     "Genetic programming is combined with program analysis
                 methods to repair bugs in off-the-shelf legacy C
                 programs. Fitness is defined using negative test cases
                 that exercise the bug to be repaired and positive test
                 cases that encode program requirements. Once a
                 successful repair is discovered, structural
                 differencing algorithms and delta debugging methods are
                 used to minimize its size. Several modifications to the
                 GP technique contribute to its success: (1) genetic
                 operations are localized to the nodes along the
                 execution path of the negative test case; (2)
                 high-level statements are represented as single nodes
                 in the program tree; (3) genetic operators use existing
                 code in other parts of the program, so new code does
                 not need to be invented. The paper describes the
                 method, reviews earlier experiments that repaired 11
                 bugs in over 60,000 lines of code, reports results on
                 new bug repairs, and describes experiments that analyze
                 the performance and efficacy of the evolutionary
                 components of the algorithm.",
  notes =        "Best paper. Gold medal HUMIES.

                 Autofix zune bug: microsoft Zune media player end of
                 year bug 31 dec 2008.

                 GECCO-2009 A joint meeting of the eighteenth
                 international conference on genetic algorithms
                 (ICGA-2009) and the fourteenth annual genetic
                 programming conference (GP-2009).

                 ACM Order Number 910092.",

Genetic Programming entries for Stephanie Forrest ThanhVu Nguyen Westley Weimer Claire Le Goues