Coevolving Programs and Unit Tests from their Specification

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

@InProceedings{Arcuri:2007:ASE,
  author =       "Andrea Arcuri and Xin Yao",
  title =        "Coevolving Programs and Unit Tests from their
                 Specification",
  booktitle =    "IEEE International Conference on Automated Software
                 Engineering (ASE)",
  year =         "2007",
  address =      "Atlanta, Georgia, USA",
  month =        nov # " 5-9",
  organisation = "IEEE",
  keywords =     "genetic algorithms, genetic programming, Automatic
                 Programming, Coevolution, Software Testing, Formal
                 Specification, Sorting, SBSE",
  DOI =          "doi:10.1145/1321631.1321693",
  abstract =     "Writing a formal specification before implementing a
                 program helps to find problems with the system
                 requirements. The requirements might be for example
                 incomplete and ambiguous. Fixing these types of errors
                 is very difficult and expensive during the
                 implementation phase of the software development cycle.
                 Although writing a formal specification is usually
                 easier than implementing the actual code, writing a
                 specification requires time, and often it is preferred,
                 instead, to use this time on the implementation. In
                 this paper we introduce for the first time a framework
                 that might evolve any possible generic program from its
                 specification. We use the Genetic Programming to evolve
                 the programs, and at the same time we exploit the
                 specifications to coevolve sets of unit tests. Programs
                 are rewarded on how many tests they do not fail,
                 whereas the unit tests are rewarded on how many
                 programs they make fail. We present and analyse four
                 different problems on which this novel technique is
                 successfully applied.",
  notes =        "http://www.cse.msu.edu/ase2007/",
}

Genetic Programming entries for Andrea Arcuri Xin Yao

Citations