  In this paper, we have developed an approach to generate test data for path
coverage based testing. The main challenge of this kind testing lies in its
ability to build efficiently such a test suite in order to minimize the number
of rejects. We address this problem with a novel divide-and-conquer approach
based on adaptive random testing strategy. Our approach takes as input the
constraints of an executable path and computes a tight over-approximation of
their associated sub-domain by using a dynamic domain partitioning approach. We
implemented this approach and got experimental results that show the practical
benefits compared to existing approaches. Our method generates less invalid
inputs and is capable of obtaining the sub-domain of many complex constraints.
