A Systematic Review of the Application and Empirical Investigation of Search-Based Test-Case Generation

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

@Article{Ali:2010:ieeeTSE,
  author =       "Shaukat Ali and Lionel C. Briand and Hadi Hemmati and 
                 Rajwinder K. Panesar-Walawege",
  title =        "A Systematic Review of the Application and Empirical
                 Investigation of Search-Based Test-Case Generation",
  journal =      "IEEE Transactions on Software Engineering",
  year =         "2010",
  volume =       "36",
  number =       "6",
  pages =        "742--762",
  month =        nov # "-" # dec,
  keywords =     "genetic algorithms, genetic programming, SBSE",
  ISSN =         "0098-5589",
  URL =          "http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5210118&isnumber=4359463",
  DOI =          "doi:10.1109/TSE.2009.52",
  size =         "22 pages",
  abstract =     "Metaheuristic search techniques have been extensively
                 used to automate the process of generating test cases
                 and thus providing solutions for a more cost-effective
                 testing process. This approach to test automation,
                 often coined as Search-based Software Testing (SBST),
                 has been used for a wide variety of test case
                 generation purposes. Since SBST techniques are
                 heuristic by nature, they must be empirically
                 investigated in terms of how costly and effective they
                 are at reaching their test objectives and whether they
                 scale up to realistic development artifacts. However,
                 approaches to empirically study SBST techniques have
                 shown wide variation in the literature. This paper
                 presents the results of a systematic, comprehensive
                 review that aims at characterising how empirical
                 studies have been designed to investigate SBST
                 cost-effectiveness and what empirical evidence is
                 available in the literature regarding SBST
                 cost-effectiveness and scalability. We also provide a
                 framework that drives the data collection process of
                 this systematic review and can be the starting point of
                 guidelines on how SBST techniques can be empirically
                 assessed. The intent is to aid future researchers doing
                 empirical studies in SBST by providing an unbiased view
                 of the body of empirical evidence and by guiding them
                 in performing well designed empirical studies.",
  notes =        "cites one GP paper:
                 \cite{Wappler:2007:ASE}.

                 TSESI-2008-09-0283",
}

Genetic Programming entries for Shaukat Ali Lionel C Briand Hadi Hemmati Rajwinder Kaur Panesar-Walawege

Citations