When quoting this document, please refer to the following
URN: urn:nbn:de:0030-drops-20165
Go to the corresponding Portal

Tettamanzi, Andrea G. B.

Fuzzy Logic Based Objective Function Construction for Evolutionary Test Generation

08351.TettamanziAndrea.Paper.2016.pdf (0.2 MB)


The test case generation problem can be stated as an optimization problem whereby the closeness of test cases to violating the postcondition of a formal specification is maximized, subject to satisfying its precondition. This is usually implemented by constructing an objective function which provides a real-valued estimate of how distant all of the constraints are from being violated, and then trying to minimize it. A problem with this approach is that such objective functions may contain plateaux, which make their minimization hard. We propose a similar approach, grounded on fuzzy logic, which uses, instead of a "distance from violation" objective function, a fuzzy degree of proximity to postcondition violation and produces plateaux-free objective functions by construction. The approach is illustrated with the help of a case study on the functional (black-box) testing of computer programs.

BibTeX - Entry

  author =	{Andrea G. B. Tettamanzi},
  title =	{Fuzzy Logic Based Objective Function Construction for Evolutionary Test Generation},
  booktitle =	{Evolutionary Test Generation},
  year =	{2009},
  editor =	{Holger Schlingloff and Tanja E. J. Vos and Joachim Wegener},
  number =	{08351},
  series =	{Dagstuhl Seminar Proceedings},
  ISSN =	{1862-4405},
  publisher =	{Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany},
  address =	{Dagstuhl, Germany},
  URL =		{},
  annote =	{Keywords: Functional testing, fuzzy logic, objective function}

Keywords: Functional testing, fuzzy logic, objective function
Seminar: 08351 - Evolutionary Test Generation
Issue Date: 2009
Date of publication: 25.05.2009

DROPS-Home | Fulltext Search | Imprint Published by LZI