  Swarm verification and parallel randomised depth-first search are very
effective parallel techniques to hunt bugs in large state spaces. In case bugs
are absent, however, scalability of the parallelisation is completely lost. In
recent work, we proposed a mechanism to inform the workers which parts of the
state space to explore. This mechanism is compatible with any action-based
formalism, where a state space can be represented by a labelled transition
system. With this extension, each worker can be strictly bounded to explore
only a small fraction of the state space at a time. In this paper, we present
the HIVE tool together with two search algorithms which were added to the
LTSmin tool suite to both perform a preprocessing step, and execute a bounded
worker search. The new tool is used to coordinate informed swarm explorations,
and the two new LTSmin algorithms are employed for preprocessing a model and
performing the individual searches.
