Fakultätsöffentliche Vorstellung des Promotionsvorhabens (Grüner Vortrag), Kevin Andrews, Ort: O27/545, Datum: 06.11.2019, Zeit: 13:00 Uhr

Process management systems support users during the execution of predefined business processes. However, when unforeseen situations occur, which are not part of the process model serving as the template for process execution, contemporary technology is often unable to offer adequate user support. One solution to this problem is to allow for ad-hoc changes to process models, i.e., changes that may be applied on the fly to a running process instance. As opposed to the widespread activity-centric process modeling paradigm, for which the support of instance-specific ad-hoc changes is well researched, there is no corresponding support for ad-hoc changes in other process support paradigms. This talk presents concepts for supporting ad-hoc changes in data-centric and data-driven processes and gives insights into the challenges to be tackled when implementing this kind of process flexibility.
One of the main challenges concerns scalability, as ad-hoc changes may affect hundreds of thousands of running instances. Therefore, the process execution engine should be inherently scalable in order to support ad-hoc changes to running process instances, in conjunction with regular process execution, on a large scale. As most currently available process management systems are incapable of scaling horizontally, a new process management system was developed utilizing microservices and actor model theory. This allows for distributed process execution by conceptually encapsulating process logic and data into multiple interacting microservices at run-time, which can be hosted transparently across entire server clusters in cloud scenarios. The corresponding design science artifact, PHILharmonicFlows, a process management system relying on the object-aware process management paradigm, is presented. PHILharmonicFlows enables both highly flexible process execution with the possibility of ad-hoc changes at runtime and horizontal scalability through the use of the microservice-based architecture.