Business Process Management: Concepts, Languages, Architectures
Business Process Management: Concepts, Languages, Architectures
On the automation of fixing software bugs
Companion of the 30th international conference on Software engineering
Correcting Deadlocking Service Choreographies Using a Simulation-Based Graph Edit Distance
BPM '08 Proceedings of the 6th International Conference on Business Process Management
Improved model management with aggregated business process models
Data & Knowledge Engineering
Petri Net Transformations for Business Processes --- A Survey
Transactions on Petri Nets and Other Models of Concurrency II
Instantaneous Soundness Checking of Industrial Business Process Models
BPM '09 Proceedings of the 7th International Conference on Business Process Management
Journal of Computer and System Sciences
A workflow net similarity measure based on transition adjacency relations
Computers in Industry
Similarity of business process models: Metrics and evaluation
Information Systems
Soundness of workflow nets: classification, decidability, and analysis
Formal Aspects of Computing
Dominance-Based Multiobjective Simulated Annealing
IEEE Transactions on Evolutionary Computation
History-aware, real-time risk detection in business processes
OTM'11 Proceedings of the 2011th Confederated international conference on On the move to meaningful internet systems - Volume Part I
Repairing process models to reflect reality
BPM'12 Proceedings of the 10th international conference on Business Process Management
Assessing the best-order for business process model refactoring
Proceedings of the 28th Annual ACM Symposium on Applied Computing
Discovering block-structured process models from event logs - a constructive approach
PETRI NETS'13 Proceedings of the 34th international conference on Application and Theory of Petri Nets and Concurrency
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As order dependencies between process tasks can get complex, it is easy to make mistakes in process model design, especially behavioral ones such as deadlocks. Notions such as soundness formalize behavioral errors and tools exist that can identify such errors. However these tools do not provide assistance with the correction of the process models. Error correction can be very challenging as the intentions of the process modeler are not known and there may be many ways in which an error can be corrected. We present a novel technique for automatic error correction in process models based on simulated annealing. Via this technique a number of process model alternatives are identified that resolve one or more errors in the original model. The technique is implemented and validated on a sample of industrial process models. The tests show that at least one sound solution can be found for each input model within a reasonable response time.