TY  - CONF
A1  - Schneid, Konrad
A1  - Kuchen, Herbert
A1  - Thöne, Sebastian
A1  - Di Bernardo, Sascha
T1  - Uncovering Data-Flow Anomalies in BPMN-Based Process-Driven Applications
T2  - Proceedings of the 36th Annual ACM Symposium on Applied Computing
N2  - 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.
KW  - BPMN
KW  - Data-Flow Anomalies
KW  - Process-Driven Application
KW  - Control-Flow Graph Analysis
Y1  - 2021
UR  - https://www.hb.fh-muenster.de/opus4/frontdoor/index/index/docId/13718
SN  - 9781450381048
SP  - 1504
EP  - 1512
PB  - Association for Computing Machinery
CY  - New York, NY, USA
ER  -