In graph transformation, the most cost-intensive phase of a transformation
execution is pattern matching, where those subgraphs of a model graph are
identified and matched which satisfy constraints prescribed by graph patterns.
Incremental pattern matching aims to improve the efficiency of this critical step
storing the set of matches of a graph transformation rule and incrementally
maintaining it as the model changes, thus eliminating the need of recalculating
existing matches of a pattern. In this paper, we propose benchmark examples
where incremental pattern matching is expected to have advantageous effect in the
application domain of model simulation and model synchronization. Moreover, we
compare the incremental graph pattern matching approach of Viatra2 with
advanced non-incremental local-search based graph pattern matching approaches
(as available in Viatra2 and GrGen).