The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Modeling Process-Driven SOAs: A View-Based Approach
|
Author(s): Huy Tran (Vienna University of Technology, Austria), Ta’id Holmes (Vienna University of Technology, Austria), Uwe Zdun (Vienna University of Technology, Austria)and Schahram Dustdar (Vienna University of Technology, Austria)
Copyright: 2009
Pages: 22
Source title:
Handbook of Research on Business Process Modeling
Source Author(s)/Editor(s): Jorge Cardoso (SAP Research, Germany)and Wil van der Aalst (Technische Universitat Eindhoven, The Netherlands)
DOI: 10.4018/978-1-60566-288-6.ch002
Purchase
|
Abstract
This chapter introduces a view-based, model-driven approach for process-driven, service-oriented architectures. A typical business process consists of numerous tangled concerns, such as the process control flow, service invocations, fault handling, transactions, and so on. Our view-based approach separates these concerns into a number of tailored perspectives at different abstraction levels. On the one hand, the separation of process concerns helps reducing the complexity of process development by breaking a business process into appropriate architectural views. On the other hand, the separation of levels of abstraction offers appropriately adapted views to stakeholders, and therefore, helps quickly re-act to changes at the business level and at the technical level as well. Our approach is realized as a model-driven tool-chain for business process development.
Related Content
Yuvika Singh, Esha Bansal, Nisha Chanana.
© 2024.
26 pages.
|
Nitish Kumar Minz, Anshika Prakash, Meenal Arora, Rishi Chaudhary, Saurav Dixit.
© 2024.
14 pages.
|
Manoj Govindaraj, Chandramowleeswaran Gnanasekaran, R. Kandavel, Parvez Khan, Sinh Duc Hoang.
© 2024.
20 pages.
|
Ravishankar Krishnan, Elantheraiyan Perumal, Manoj Govindaraj, Logasakthi Kandasamy.
© 2024.
22 pages.
|
Sanjay Taneja, Rishi Prakash Shukla, Amandeep Singh.
© 2024.
11 pages.
|
Mune Moğol Sever.
© 2024.
23 pages.
|
Sujay Vikram Singh, Terrance Ancheary, Anish Mondal, Shashank Rajauria.
© 2024.
17 pages.
|
|
|