Discovering process models from execution history by graph matching

Process engineering and workflow analysis both aim to enhance business operations, product manufacturing and software development by applying proven process models to solve individual problem cases. However, most applications assume that a process model already exists and is available. In many situations, though, the more important and interesting problem to solve is that of discovering or recovering the model by reverse engineering given an abundance of execution logs or history. In this paper, a new algorithmic solution is presented for process model discovery, which is treated as a special case of the Maximal Overlap Sets problem in graph matching. The paradigm of planning and scheduling by resource management is used to tackle the combinatorial complexity and to achieve efficiency and practicality in real world applications. The effectiveness of the algorithm, for this generally NP (nondeterministic polynomial) problem, is demonstrated with a broad set of experimental results.