A log induced change mining method for fault diagnosis using structure causality in BPMSs
FANG Huan
ZHANG Yuan
WU Qi-lin
Abstract：In business process management systems(BPMSs),impending faults could change the behavior of the system;thus,it is necessary to investigate the methods that identify the minimum change region of the system due to faults,which is of great importance for the robustness of BPMSs.In this paper,we propose a log induced change mining method,named the minimal structure fault region identification (MSFRI) method,which has the primary goal to identify the structural causality for given behavior changes.The MSFRI method is applied in free-choice net Petri nets systems,and six characteristic change patterns are formalized,which provide structural causality foundations for change mining.The method locates the fault regions that deduces the behavior changes,which have the smallest number of places and transitions in a Petri net system.The identification of these regions is helpful for change mining.Our novel MSFRI method provides a structural perspective for analyzing the causality for behavior changes,such as an impending fault in BPMSs.
Keywords：behavioral profileschange miningfault detection and diagnosisPetri netsstructural causality
Publication Date：2018-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：10( 1167-1176 )