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.
@InProceedings{tettamanzi:DagSemProc.08351.4, author = {Tettamanzi, Andrea G. B.}, title = {{Fuzzy Logic Based Objective Function Construction for Evolutionary Test Generation}}, booktitle = {Evolutionary Test Generation}, pages = {1--11}, series = {Dagstuhl Seminar Proceedings (DagSemProc)}, ISSN = {1862-4405}, year = {2009}, volume = {8351}, editor = {Holger Schlingloff and Tanja E. J. Vos and Joachim Wegener}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08351.4}, URN = {urn:nbn:de:0030-drops-20165}, doi = {10.4230/DagSemProc.08351.4}, annote = {Keywords: Functional testing, fuzzy logic, objective function} }
Feedback for Dagstuhl Publishing