The HIVE Tool for Informed Swarm State Space Exploration

The HIVE Tool for Informed Swarm State Space Exploration

Blog Article

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 Floor Mops - Mops 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 Riding Coats 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.