We introduce targeted property-based testing, an enhanced form of
property-based testing that aims to make the input generation component of a
property-based testing tool guided by a search strategy rather than being
completely random. Thus, this testing technique combines the advantages
of both search-based and property-based testing.

We demonstrate the technique with the framework we have built, called Target,
and show its effectiveness on three case studies. The first of them demonstrates
how Target can employ simulated annealing to generate sensor network topologies
that form configurations with high energy consumption. The second case study
shows how the generation of routing trees for a wireless network equipped with
directional antennas can be guided to fulfill different energy metrics.
The third case study employs Target to test the noninterference property of
information-flow control abstract machine designs, and compares it with a
sophisticated hand-written generator for programs of these abstract machines.