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Bridging the Gap between Business Process Models and Service Composition Specifications

Bridging the Gap between Business Process Models and Service Composition Specifications
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Author(s): Stephan Buchwald (Daimler AG, Germany), Thomas Bauer (Daimler AG, Germany)and Manfred Reichert (University of Ulm, Germany)
Copyright: 2012
Pages: 30
Source title: Service Life Cycle Tools and Technologies: Methods, Trends and Advances
Source Author(s)/Editor(s): Jonathan Lee (National Central University, Taiwan), Shang-Pin Ma (National Taiwan Ocean University, Taiwan)and Alan Liu (National Chung Cheng University, Taiwan)
DOI: 10.4018/978-1-61350-159-7.ch007

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Abstract

Fundamental goals of any Service Oriented Architecture (SOA) include the flexible support and adaptability of business processes as well as improved business-IT alignment. Existing approaches, however, have failed to fully meet these goals. One of the major reasons for this deficiency is the gap that exists between business process models on the one hand and workflow specifications and implementations (e.g., service composition schemes) on the other hand. In practice, each of these two perspectives has to be regarded separately. In addition, even simple changes to one perspective (e.g. due to new regulations or organizational change) require error-prone, manual re-editing of the other one. Over time, this leads to degeneration and divergence of the respective models and specifications. This aggravates maintenance and makes expensive refactoring inevitable. This chapter presents a flexible approach for aligning business process models with workflow specifications. In order to maintain the complex dependencies that exist between high-level business process models (as used by domain experts) and technical workflow specifications (i.e., service composition schemas), respectively, (as used in IT departments) we introduce an additional model layer – the so-called system model. Furthermore, we explicitly document the mappings between the different levels (e.g., between business process model and system model). This simplifies model adoptions by orders of magnitudes when compared to existing approaches.

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