C-3PA: Streaming Conformance, Confidence and Completeness in Prefix-Alignments

The aim of streaming conformance checking is to find discrepancies between process executions on streaming data and the reference process model. The state-of-the-art output from streaming conformance checking is a prefix-alignment. However, current techniques that output a prefix-alignment are unable to handle warm-starting scenarios. Further, no indication is given of how close the trace is to termination—a highly relevant measure in a streaming setting. This paper introduces a novel approximate streaming conformance checking algorithm that enriches prefix-alignments with confidence and completeness measures. Empirical tests on synthetic and real-life datasets demonstrate that the new method outputs prefix-alignments that have a cost that is highly correlated with the output from the stateof-the-art optimal prefix-alignments. Furthermore, the method is able to handle warm-starting scenarios and indicate the confidence level of the
prefix-alignment. A stress test shows that the method is well-suited for fast-paced event streams.