Raun, KristoNielsen, MaxBurattin, AndreaAwad, Ahmed2025-05-072025-05-072023Raun, K., Nielsen, M., Burattin, A., Awad, A. (2023). C-3PA: Streaming Conformance, Confidence and Completeness in Prefix-Alignments. In: Indulska, M., Reinhartz-Berger, I., Cetina, C., Pastor, O. (eds) Advanced Information Systems Engineering. CAiSE 2023. Lecture Notes in Computer Science, vol 13901. Springer, Cham.https://bspace.buid.ac.ae/handle/1234/2943The aim of streaming conformance checking is to find dis crepancies between process executions on streaming data and the refer ence process model. The state-of-the-art output from streaming confor mance 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 state of-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.enStreaming conformance checking,Prefix-alignments,Warm-starting,Confidence,Data streamsArticlehttps://doi.org/10.1007/978-3-031-34560-9_26