GenProg: A Generic Method for Automatic Software Repair

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{DBLP:journals/tse/GouesNFW12,
  author =       "Claire {Le Goues} and ThanhVu Nguyen and 
                 Stephanie Forrest and Westley Weimer",
  title =        "{GenProg}: A Generic Method for Automatic Software
                 Repair",
  year =         "2012",
  journal =      "IEEE Transactions on Software Engineering",
  volume =       "38",
  number =       "1",
  pages =        "54--72",
  month =        jan # "-" # feb,
  keywords =     "genetic algorithms, genetic programming, sbse,
                 Automatic programming, corrections, testing and
                 debugging",
  URL =          "http://www.cs.virginia.edu/~weimer/p/weimer-tse2012-genprog.pdf",
  DOI =          "doi:10.1109/TSE.2011.104",
  size =         "19 pages",
  abstract =     "This paper describes GenProg, an automated method for
                 repairing defects in off-the-shelf, legacy programs
                 without formal specifications, program annotations, or
                 special coding practices. GenProg uses an extended form
                 of genetic programming to evolve a program variant that
                 retains required functionality but is not susceptible
                 to a given defect, using existing test suites to encode
                 both the defect and required functionality. Structural
                 differencing algorithms and delta debugging reduce the
                 difference between this variant and the original
                 program to a minimal repair. We describe the algorithm
                 and report experimental results of its success on 16
                 programs totalling 1.25 M lines of C code and 120K
                 lines of module code, spanning eight classes of
                 defects, in 357 seconds, on average. We analyse the
                 generated repairs qualitatively and quantitatively to
                 demonstrate that the process efficiently produces
                 evolved programs that repair the defect, are not
                 fragile input memorisations, and do not lead to serious
                 degradation in functionality.",
  notes =        "S/w maintenance 90percent of cost of software project.
                 Auto bug fix. localise which C source statements
                 genetic operators act on. CIL abstract syntax tree AST
                 and weighted linear path. Always correct syntax, but
                 may not compile.

                 deterministic bugs. delta debugging. 100 trials. Very
                 small number of positive and negative test cases. xdiff
                 converted to diff patch format. Crossover and mutation,
                 pop=40, gen=10. page62 pmut<0.12. Fig 9 linear scaling.
                 Online repair, www web http lighttpd examples. SPIKE
                 black box fuzz testing.

                 Cited by \cite{Tan:ICSE:2015}",
  bibsource =    "DBLP, http://dblp.uni-trier.de",
}

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

Citations