Fuzzy Logic Based Objective Function Construction for Evolutionary Test Generation

Author Andrea G. B. Tettamanzi

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Andrea G. B. Tettamanzi

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Andrea G. B. Tettamanzi. Fuzzy Logic Based Objective Function Construction for Evolutionary Test Generation. In Evolutionary Test Generation. Dagstuhl Seminar Proceedings, Volume 8351, pp. 1-11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)


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.
  • Functional testing
  • fuzzy logic
  • objective function


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