Detection of Dataflow Anomalies in Business Process An Overview of Modeling Approaches

Most research focus on control flow modeling when modeling and analyzing business process models, but less attention is paid to data flow. However, data flow and control flow are both essential in process modeling. Thus, the data flow modeling and verification have a great importance in detecting anomalies. In this study, some recent approaches for anomaly detection has reviewed. The first is an analytical approach for detecting and eliminating three types of data-flow errors that formally establish the correctness criteria for data-flow modeling. The second formulates the data-flow modeling and verification using a Petri Net based approach. The third one presents an ad hoc approach to detect data modelling errors in business process models by applying for an active help using a DataRecord concept. We explain for each approach its proper method and tools. We then compare and analyze each one of them to discover the added-value of each approach.