Combining Stochastic Grammars and Genetic Programming for Coverage Testing at the System Level

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

@InProceedings{Kifetew:2014:SSBSE,
  author =       "Fitsum Meshesha Kifetew and Roberto Tiella and 
                 Paolo Tonella",
  title =        "Combining Stochastic Grammars and Genetic Programming
                 for Coverage Testing at the System Level",
  booktitle =    "Proceedings of the 6th International Symposium, on
                 Search-Based Software Engineering, SSBSE 2014",
  year =         "2014",
  editor =       "Claire {Le Goues} and Shin Yoo",
  volume =       "8636",
  series =       "LNCS",
  pages =        "138--152",
  address =      "Fortaleza, Brazil",
  month =        "26-29 " # aug,
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, SBSE, grammar
                 based testing",
  isbn13 =       "978-3-319-09939-2",
  URL =          "http://www.springer.com/computer/swe/book/978-3-319-09939-2",
  DOI =          "doi:10.1007/978-3-319-09940-8_10",
  size =         "15 pages",
  abstract =     "When tested at the system level, many programs require
                 complex and highly structured inputs, which must
                 typically satisfy some formal grammar. Existing
                 techniques for grammar based testing make use of
                 stochastic grammars that randomly derive test sentences
                 from grammar productions, trying at the same time to
                 avoid unbounded recursion. In this paper, we combine
                 stochastic grammars with genetic programming, so as to
                 take advantage of the guidance provided by a coverage
                 oriented fitness function during the sentence
                 derivation and evolution process. Experimental results
                 show that the combination of stochastic grammars and
                 genetic programming outperforms stochastic grammars
                 alone.",
  notes =        "StGP, EvoSuite, Calc, MDSL, JavaScript Rhino, branch
                 coverage, GA/GP testsuite, test cases. Fitness using
                 minimum branch distance (p148 'not particularly
                 useful'?). Mutation testing. Grammar learning
                 Lari+Young 1990. Beyene&Andrews ICST-2012",
}

Genetic Programming entries for Fitsum Meshesha Kifetew Roberto Tiella Paolo Tonella

Citations