Rule randomisation and its application to logic-based workflow verification

Workflow verification has been a well-studied research topic during the past few years. Theorem proof-based approaches to workflow verification have become popular due to several advantages including being based on formal characterisation with rigorous and unambiguous inference mechanisms. However, a common problem with these inference mechanisms is combinatorial explosions, which forms a major performance hurdle to workflow verification systems based on inference. In this paper, we study how randomisation enables reuse and reduces processing time in logic-based workflow verification approaches. In particular, we look at a propositional logic-based workflow verification technique. For the logic inference rules, which are used to infer new truthful propositions from existing truthful propositions in this logic, we apply randomisation to the inference rules after each verification task such that new inference rules, reflecting the componentised verification, are added to the inference rule sets. We also review the savings gained by verifying a workflow pattern and provide a theoretical analysis.