Selection and evaluation of test data sets based on genetic programming

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

  title =        "Selection and evaluation of test data sets based on
                 genetic programming",
  author =       "Maria Claudia F. P. Emer and Silvia Regina Vergilio",
  year =         "2002",
  identifier =   "sbes2002article006",
  language =     "por",
  rights =       "Sociedade Brasileira de Computa{\c c}{\~a}o",
  source =       "sbes2002",
  booktitle =    "XVI Simposio Brasileiro de Engenharia de Software",
  pages =        "82--97",
  address =      "Gramado, Rio Grande do Sul, Brasil",
  keywords =     "genetic algorithms, genetic programming, SBSE, GPBT,
                 GPtesT, search based testing, SE, mutation testing",
  URL =          "",
  size =         "16 pages",
  abstract =     "A testing criterion is a predicate to be satisfied and
                 generally addresses two important questions related to:
                 1) the selection of test cases capable of revealing as
                 many faults as possible; and 2) the evaluation of a
                 test set to consider the test ended. Studies show that
                 fault based criteria, such as mutation testing, are
                 very efficacious, but very expensive in terms of the
                 number of test cases. Mutation testing uses mutation
                 operators to generate alternatives for the program P
                 under test. The goal is to derive test cases to
                 producing different behaviours in P and its
                 alternatives. 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)
                 to derive alternatives for testing P and describes two
                 GP-based test procedures for selection and evaluation
                 of test data. Experimental results show the GP approach
                 applicability and allow comparison with mutation
  notes =        "
                 triangle, chameleon and C, Grammar for factorial
                 program, Proteum, Equivalent mutants",

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