Arash Mehrmand MSE-2009:20, pp. 43. COM/School of Computing, 2009.
Software testing is an expensive process, which is
vital in the industry. Construction of the test-data in software
testing requires the major cost and knowing which method to
use in order to generate the test data is very important. This
paper discusses the performance of search-based algorithms
(preferably genetic algorithm) versus random testing, in software
test-data generation. A factorial experiment is designed
so that, we have more than one factor for each experiment we
make. Although many researches have been done in the area
of automated software testing, this research differs from all of
them due to sample programs (SUTs) which are used. Since
the program generation is automatic as well, Grammatical
Evolution is used to guide the program generations. They are
not goal based, but generated according to the grammar we
provide, with different levels of complexity. Genetic algorithm
is first applied to programs, then we apply random testing.
Based on the results which come up, this paper recommends
one method to use for software testing, if the SUT has the
same conditions as we had in this study. SUTs are not like
the sample programs, provided by other studies since they are
generated using a grammar.