Abstract:
In search based test data generation, the problem of test data generation is reduced to that of
function minimization or maximization.Traditionally, for branch testing, the problem of test data
generation has been formulated as a minimization problem. In this paper we define an alternate
maximization formulation and experimentally compare it with the minimization formulation. We
use a genetic algorithm as the search technique and in addition to the usual genetic algorithm
operators we also employ the path prefix strategy as a branch ordering strategy and memory and
elitism. Results indicate that there is no significant difference in the performance or the coverage
obtained through the two approaches and either could be used in test data generation when
coupled with the path prefix strategy, memory and elitism.