@InProceedings{YanoMartSous:2010:GeFeTe,
author = "Yano, T. and Martins, E. and Sousa, F. L.",
affiliation = "Institute of Computing, State University of Campinas, UNICAMP,
Campinas, SP, Brazil and Institute of Computing, State University
of Campinas, UNICAMP, Campinas, SP, Brazil and {Instituto Nacional
de Pesquisas Espaciais (INPE)}",
title = "Generating feasible test paths from an executable model using a
multi-objective approach",
year = "2010",
pages = "236--239",
organization = "3rd International Conference on Software Testing, Verification,
and Validation Workshops, 3. (ICSTW)",
keywords = "Executable model, Feasible path, Model-based testing,
Multi-objective optimization, Behavior model, Evolutionary
approach, Executable model, Extended finite state machine,
Infeasible paths, Meta heuristics, Multi objective, Open problems,
Path models, Size minimization, Test data generation, Test
purpose, Test sequence, Testing technique, White-box testing.",
abstract = "Search-based testing techniques using metaheuristics, like
evolutionary algorithms, has been largely used for test data
generation, but most approaches were proposed for white-box
testing. In this paper we present an evolutionary approach for
test sequence generation from a behavior model, in particular,
Extended Finite State Machine. An open problem is the production
of infeasible paths, as these should be detected and discarded
manually. To circumvent this problem, we use an executable model
to obtain feasible paths dynamically. An evolutionary algorithm is
used to search for solutions that cover a given test purpose,
which is a transition of interest. The target transition is used
as a criterion to get slicing information, in this way, helping to
identify the parts of the model that affect the test purpose. We
also present a multi-objective search: the test purpose coverage
and the sequence size minimization, as longer sequences require
more effort to be executed.",
conference-location = "Paris",
conference-year = "6 - 10 Apr. 2010",
doi = "10.1109/ICSTW.2010.52",
url = "http://dx.doi.org/10.1109/ICSTW.2010.52",
isbn = "978-076954050-4",
language = "en",
targetfile = "Yano_Generation.pdf",
volume = "Article number 5463651",
urlaccessdate = "27 abr. 2024"
}