MSE Research Project Database

Automated Process Model Repair


Project Leader: Artem Polyvyanyy
Primary Contact: Artem Polyvyanyy (artem.polyvyanyy@unimelb.edu.au)
Keywords:
Disciplines: Computing and Information Systems
Domains:

Process model repair is concerned with this problem in process mining: Given an event log of a process-aware information system, i.e., a recorded sequence of activities performed by the system, that deviates and, hence, cannot be replayed by the system, automatically transform the design of the system so that the transformed system can replay the event log. Process model repair allows keeping models of process-aware information systems in sync with observed executions. The reasons for the deviations between designed and observed executions of systems are manifold. For example, a deviation can be caused by a decision to perform an ad hoc activity while executing an outdated business process that no longer caters for all the requirements, or may stem from a bypass of a recognized problem in the design. 

The study of the process model repair problem is an integral part of our broader research program on design of automated methods for management of process knowledge within organisations.

Current research interests in process model repair include:

  • Impact-driven process model repair;
  • Techniques for process model repair;
  • Quality metrics of process model repair;
  • Empirical studies on process model repair.

Concrete outcomes of a PhD project will depend on the specific path the project will follow and may include new techniques, algorithms, and methodologies for solving the process model repair problem.


Recent publications:

Artem Polyvyanyy, Andreas Solti, Matthias Weidlich, Claudio Di Ciccio, and Jan Mendling
Behavioural Quotients for Precision and Recall in Process Mining.
March, 2018. http://hdl.handle.net/11343/208876

Artem Polyvyanyy, Wil M.P. van der Aalst, Arthur H.M. ter Hofstede, and Moe T. Wynn.
Impact-Driven Process Model Repair. ACM Transactions on Software Engineering and Methodology (TOSEM), 2016. http://hdl.handle.net/11343/209075