Uncovering Data-Flow Anomalies in BPMN-Based Process-Driven Applications

  • Process-Driven Applications flourish through the interaction between an executable BPMN process model, human tasks, and external software services. All these components operate on shared process data, so it is even more important to check the correct data flow. However, data flow is in most cases not explicitly defined but hidden in model elements, form declarations, and program code. This paper elaborates on data-flow anomalies acting as indicators for potential errors and how such anomalies can be uncovered despite implicit and hidden data-flow definitions. By considering an integrated view, it goes beyond other approaches which are restricted to separate data-flow analysis of either process model or source code. The main idea is to merge call graphs representing programmed services into a control-flow representation of the process model, to label the resulting graph with associated data operations, and to detect anomalies in that labeled graph using a dedicated data-flow analysis. The applicability of the solution is demonstrated by a prototype designed for the Camunda BPM platform.
Bitte benutzen Sie diese Referenz, um auf diese Ressource zu verweisen:

Export metadata

Additional Services

Author:Konrad Schneid, Herbert Kuchen, Sebastian Thöne, Sascha Di Bernardo
Parent Title (English):Proceedings of the 36th Annual ACM Symposium on Applied Computing
Publisher:Association for Computing Machinery
Place of publication:New York, NY, USA
Document Type:Conference Proceeding
Date of Publication (online):2021/04/26
Year of first Publication:2021
Provider of the Publication Server:FH Münster - University of Applied Sciences
Release Date:2021/04/26
Tag:BPMN; Control-Flow Graph Analysis; Data-Flow Anomalies; Process-Driven Application
First Page:1504
Last Page:1512
Faculties:Wirtschaft (MSB)
Publication list:Schneid, Konrad
Thöne, Sebastian
Licence (German):License LogoBibliographische Daten