I Will Survive: An Event-driven Conformance Checking Approach Over Process Streams.

Online conformance checking deals with finding discrepancies between real-life and modeled behavior on data streams. The current state-of-the-art output of online conformance checking is a prefix-alignment, which is used for pinpointing the exact deviations in terms of the trace and the model while accommodating a trace's unknown termination in an online setting. Current methods for producing prefix-alignments are computationally expensive and hinder the applicability in real-life settings. This paper introduces a new approximate algorithm - I Will Survive (IWS). The algorithm utilizes the trie data structure to improve the calculation speed, while remaining memory-efficient. Comparative analysis on real-life and synthetic datasets shows that the IWS algorithm can achieve an order of magnitude faster execution time while having a smaller error cost, compared to the current state of the art. In extreme cases, the IWS finds prefix-alignments roughly three orders of magnitude faster than previous approximate methods. The IWS algorithm includes a discounted decay time setting for more efficient memory usage and a look-ahead limit for improving computation time. Finally, the algorithm is stress tested for performance using a simulation of high-traffic event streams.