Ontology-based Multi-Objective Evolutionary Algorithm for Deriving Software Services from Business Process Model

Abstract

Various approaches uses business process models as starting point to derive software services. The first and the important task for developing service-oriented models is service identification. However, the majority of existing methods for service identification are developed manually because, on the one hand, they are based on the competence of the developers and, on the other hand, the business process models do not comprise sufficient knowledge to identify services automatically. The integration of Business Process Modeling (BPM), Model-Driven Development (MDD), and Ontology-based Semantic Annotation (OSA) allows the automation of the SOA (Service-Oriented Architecture) services development. Three steps are used for developing an SOA solution: service identification, service specification and finally service realization. In this paper, the authors illustrate a method called MOOSI (Multi-Objective Optimization-based Service Identification) that automatically identifies the architecturally significant elements from an annotated business process model in order to specify service model artifacts. The main goal of this work is to support the automation of the development process of service-oriented enterprise information system. The implementation results of our proposed method are discussed. This result shows that MOOSI can achieve high performance in terms of execution time and important quality in terms of modularization quality of identified services compared with other solution.