Strongly-typed genetic programming and purity analysis: input domain reduction for evolutionary testing problems

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Jose Carlos {Bregieiro Ribeiro} and 
                 Mario Alberto Zenha-Rela and Francisco {Fernandez de Vega}",
  title =        "Strongly-typed genetic programming and purity
                 analysis: input domain reduction for evolutionary
                 testing problems",
  booktitle =    "GECCO '08: Proceedings of the 10th annual conference
                 on Genetic and evolutionary computation",
  year =         "2008",
  editor =       "Maarten Keijzer and Giuliano Antoniol and 
                 Clare Bates Congdon and Kalyanmoy Deb and Benjamin Doerr and 
                 Nikolaus Hansen and John H. Holmes and 
                 Gregory S. Hornby and Daniel Howard and James Kennedy and 
                 Sanjeev Kumar and Fernando G. Lobo and 
                 Julian Francis Miller and Jason Moore and Frank Neumann and 
                 Martin Pelikan and Jordan Pollack and Kumara Sastry and 
                 Kenneth Stanley and Adrian Stoica and El-Ghazali Talbi and 
                 Ingo Wegener",
  isbn13 =       "978-1-60558-130-9",
  pages =        "1783--1784",
  address =      "Atlanta, GA, USA",
  URL =          "",
  DOI =          "doi:10.1145/1389095.1389439",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  month =        "12-16 " # jul,
  keywords =     "genetic algorithms, genetic programming, Input domain
                 reduction, search-based test case generation,
                 strongly-Typed genetic programming, Search-based
                 software engineering: Poster, Testing, Debugging,
                 Testing tools, data generators, coverage testing,
                 stack, bitset, STGP, EMCDG, IDR",
  abstract =     "Search-based test case generation for object-oriented
                 software is hindered by the size of the search space,
                 which encompasses the arguments to the implicit and
                 explicit parameters of the test object's public
                 methods. The performance of this type of search
                 problems can be enhanced by the definition of adequate
                 Input Domain Reduction strategies. The focus of our
                 on-going work is on employing evolutionary algorithms
                 for generating test data for the structural
                 unit-testing of Java programs. Test cases are
                 represented and evolved using the Strongly-Typed
                 Genetic Programming paradigm; Purity Analysis is
                 particularly useful in this situation because it
                 provides a means to automatically identify and remove
                 Function Set entries that do not contribute to the
                 definition of interesting test scenarios. Categories
                 and Subject Descriptors",
  notes =        "GECCO-2008 A joint meeting of the seventeenth
                 international conference on genetic algorithms
                 (ICGA-2008) and the thirteenth annual genetic
                 programming conference (GP-2008).

                 ACM Order Number 910081. Also known as \cite{1389439}",

Genetic Programming entries for Jose Carlos Bregieiro Ribeiro Mario Alberto Zenha-Rela Francisco Fernandez de Vega