Selection and Evaluation of Test Data Based on Genetic Programming

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

@Article{emer:2003:SQJ,
  author =       "Maria Claudia F. P. Emer and Silvia Regina Vergilio",
  title =        "Selection and Evaluation of Test Data Based on Genetic
                 Programming",
  journal =      "Software Quality Journal",
  year =         "2003",
  volume =       "11",
  number =       "2",
  pages =        "167--186",
  month =        jun,
  keywords =     "genetic algorithms, genetic programming, evolutionary
                 computation, testing criteria, mutation analysis, SBSE,
                 software engineering",
  DOI =          "doi:10.1023/A:1023772729494",
  size =         "20 pages",
  abstract =     "In the literature, we find several criteria that
                 consider different aspects of the program to guide the
                 testing, a fundamental activity for software quality
                 assurance. They address two important questions: how to
                 select test cases to reveal as many fault as possible
                 and how to evaluate a test set T and end the test.
                 Fault-based criteria, such as mutation testing, use
                 mutation operators to generate alternatives for the
                 program P being tested. The goal is to derive test
                 cases capable of producing different behaviors in P and
                 its alternatives. However, this approach usually does
                 not allow the test of interaction between faults since
                 the alternative differs from P by a simple
                 modification. This work explores the use of Genetic
                 Programming (GP), a field of Evolutionary Computation,
                 to derive alternatives for testing P and introduces two
                 GP-based procedures for selection and evaluation of
                 test data. The procedures are related to the above
                 questions, usually addressed by most testing criteria
                 and tools. A tool, named GPTesT, is described and
                 results from an experiment using this tool are also
                 presented. The results show the applicability of our
                 approach and allow comparison with mutation testing.",
  notes =        "Article ID: 5122058

                 Interactive tool incorporating GP. GPTesT (C++
                 UML).

                 Chameleon \cite{Spinosa:2001:gtgp} grammar based
                 generates C programs. {"}Control over anomalous code
                 (overflow, infinite loop among others){"} p171.
                 {"}divide by zero{"} p177.

                 v. Proteum (71 SE mutation operators)

                 GPBT. cmm (common multiple), fat (factorial), max, cmd
                 (common divisor)

                 Computer Science Department, Federal University of
                 Parana?UFPR CP: 19081, 81531-970, Curitiba, Brazil
                 mpereira@inf.ufpr.br

                 ",
}

Genetic Programming entries for Maria Claudia Figueiredo Pereira Emer Silvia Regina Vergilio

Citations