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Data & Knowledge Engineering - Special issue on ER '96
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Information Systems - The 11th international conference on advanced information systems engineering (CAiSE*
Verification support for workflow design with UML activity graphs
Proceedings of the 24th International Conference on Software Engineering
Distributed and Parallel Databases
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EDOC '00 Proceedings of the 4th International conference on Enterprise Distributed Object Computing
Relaxed Soundness of Business Processes
CAiSE '01 Proceedings of the 13th International Conference on Advanced Information Systems Engineering
An Alternative Way to Analyze Workflow Graphs
CAiSE '02 Proceedings of the 14th International Conference on Advanced Information Systems Engineering
A Novel Graph Reduction Algorithm to Identify Structural Conflicts
HICSS '02 Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02)-Volume 9 - Volume 9
Automatic Control of Workflow Processes Using ECA Rules
IEEE Transactions on Knowledge and Data Engineering
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Data & Knowledge Engineering
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Data & Knowledge Engineering
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Data & Knowledge Engineering
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VLHCC '08 Proceedings of the 2008 IEEE Symposium on Visual Languages and Human-Centric Computing
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Data & Knowledge Engineering
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ATVA'05 Proceedings of the Third international conference on Automated Technology for Verification and Analysis
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BPM'06 Proceedings of the 4th international conference on Business Process Management
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BPM'05 Proceedings of the 3rd international conference on Business Process Management
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IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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ACM Transactions on Management Information Systems (TMIS)
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Data & Knowledge Engineering
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Journal of Systems and Software
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Data & Knowledge Engineering
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Workflow analysis is indispensable to capture modeling errors in workflow designs. While several workflow analysis approaches have been defined previously, these approaches do not give precise feedback, thus making it hard for a designer to pinpoint the exact cause of modeling errors. In this paper we introduce a novel approach for analyzing and diagnosing workflows based on integer programming (IP). Each workflow model is translated into a set of IP constraints. Faulty control flow connectors can be easily detected using the approach by relaxing the corresponding constraints. We have implemented this diagnosis approach in a tool called DiagFlow which reads and diagnoses XPDL models using an existing open source IP solver as a backend. We show that the diagnosis approach is correct and illustrate it with realistic examples. Moreover, the approach is flexible and can be extended to handle a variety of new constraints, as well as to support new workflow patterns. Results of testing on large process models show that DiagFlow outperforms a state of the art tool like Woflan in terms of the solution time.