Aris-Business Process Modeling
Aris-Business Process Modeling
Design Methods for Software Systems: YOURDON, Statemate and Uml
Design Methods for Software Systems: YOURDON, Statemate and Uml
The many faces of publish/subscribe
ACM Computing Surveys (CSUR)
A Taxonomy and Catalog of Runtime Software-Fault Monitoring Tools
IEEE Transactions on Software Engineering
Adaptive quality of service management for enterprise services
ACM Transactions on the Web (TWEB)
Beyond Control-Flow: Extending Business Process Configuration to Roles and Objects
ER '08 Proceedings of the 27th International Conference on Conceptual Modeling
Supporting the Diversity of B2B E-Contracting Processes
International Journal of Electronic Commerce
Business Information Systems: Analysis, Design & Practice
Business Information Systems: Analysis, Design & Practice
Dimensions of coupling in middleware
Concurrency and Computation: Practice & Experience
Modern Business Process Automation: YAWL and its Support Environment
Modern Business Process Automation: YAWL and its Support Environment
Modeling control objectives for business process compliance
BPM'07 Proceedings of the 5th international conference on Business process management
Requirements-driven design and configuration management of business processes
BPM'07 Proceedings of the 5th international conference on Business process management
Comprehensive Monitoring of BPEL Processes
IEEE Internet Computing
Capturing variability in business process models: the Provop approach
Journal of Software Maintenance and Evolution: Research and Practice - Best papers from the BPM 2008 Workshops
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Mass-customization challenges the one-size-fits-all assumption of mass production, allowing customers to specify the options that best fit their requirements when choosing a product or a service. In business process management, to achieve mass-customization, providers offer to their customers the opportunity to customize the way in which a process will be enacted. We focus on monitoring as a specific customization aspect. We propose a multi-dimensional classification of modeling patterns for customized monitoring infrastructures. Patterns enable the provider to offer a set of customizable options to customers and design a monitoring infrastructure that fits the preferences specified by customers on such options. An example in the online advertising industry demonstrates how our framework can improve the services currently offered by providers.