Discovering models of software processes from event-based data
ACM Transactions on Software Engineering and Methodology (TOSEM)
Production workflow: concepts and techniques
Production workflow: concepts and techniques
Workflow management: models, methods, and systems
Workflow management: models, methods, and systems
Open Source Development with CVS
Open Source Development with CVS
Mining Process Models from Workflow Logs
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Process Miner - A Tool for Mining Process Schemes from Event-Based Data
JELIA '02 Proceedings of the European Conference on Logics in Artificial Intelligence
DEXA '98 Proceedings of the 9th International Workshop on Database and Expert Systems Applications
Workflow-Based Process Monitoring and Controlling ¾ Technical and Organizational Issues
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 6 - Volume 6
Workflow mining: a survey of issues and approaches
Data & Knowledge Engineering
Process mining: a research agenda
Computers in Industry - Special issue: Process/workflow mining
International Journal of Computer Integrated Manufacturing
Discovering protocols and organizational structures in workflows
NOTERE '08 Proceedings of the 8th international conference on New technologies in distributed systems
Process mining framework for software processes
ICSP'07 Proceedings of the 2007 international conference on Software process
Process mining and petri net synthesis
BPM'06 Proceedings of the 2006 international conference on Business Process Management Workshops
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Current enterprises spend much effort to obtain precise models of their system engineering processes in order to improve the process capability of the organization. The manual design of workflow models is complicated, time-consuming and error-prone; capabilities of human beings in detecting discrepancies between the actual process and the process model are rather limited. Therefore, automatic techniques for deriving these models are becoming more and more important. In this paper, we present an idea that exploits the user interaction with a version management system for the incremental automatic derivation, refinement and analysis of process models. Though this idea is not fully worked out yet, we sketch the architecture of the solution and the algorithms for the main steps of incremental automatic derivation of process models.