Pattern matching is essential in many applications such as information retrieval, logic programming, theorem-proving, term rewriting and DNA-computing. It usually breaks down into two categories: root and complete pattern matching. Root matching determines whether a subject term is an instance of a pattern in a pattern set while complete matching determines whether a subject term contains a sub-term that is an instance of a pattern in a pattern set. For the sake of efficiency, root pattern matching need to be deterministic and lazy. Furthermore, complete pattern matching also needs to be parallel. Unlike root pattern matching, complete matching received little interest from the researchers of the field. In this paper, we present a novel deterministic multi-threaded complete matching method. This method subsumes a deterministic lazy root matching technique that was developped by the authors in an earlier work. We evaluate the performance of proposed method using theorem-proving and DNA-computing applications.
Adaptive Pattern Matching with Reinforcement Learning for Dynamic Graphs
