DocumentCode :
256111
Title :
Services derivation from business process: A PSO-based multi-objective approach
Author :
El Amine Chergui, Mohamed ; Benslimane, Sidi Mohamed
Author_Institution :
Comput. Sci. Dept., Djillali Liabes Univ., Sidi Bel Abbès, Algeria
fYear :
2014
fDate :
14-16 April 2014
Firstpage :
582
Lastpage :
588
Abstract :
Software module clustering is generally a difficult and challenging problem in software engineering. In the same way, service identification plays a critical role in service engineering. Existing Service identification approaches are often prescriptive and based on the architect´s experience thus could result in non-optimal designs which results in complicated dependencies between services. In this paper we proposes top down approach to identify automatically services from business process by using several design metrics. Service boundaries are identified from business processes by automated search, guided by a multi-objective fitness function and using a clustering combinatorial particle swarm optimization algorithm. In order to evaluate the effectiveness of the proposed approach, a set of experiments were performed. The experimentation results of this empirical study denotes that our approach achieves better results in term of performance and convergence speed.
Keywords :
business data processing; particle swarm optimisation; software engineering; PSO-based multiobjective approach; business process; combinatorial particle swarm optimization algorithm; design metrics; multiobjective fitness function; nonoptimal designs; service identification; software engineering; software module clustering; Business; Measurement; Optimization; Particle swarm optimization; Semantics; Service-oriented architecture; Business Process Modeling; Combinatorial Particle Swarm Optimization; Service Identification; Service Oriented Architecture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia Computing and Systems (ICMCS), 2014 International Conference on
Conference_Location :
Marrakech
Print_ISBN :
978-1-4799-3823-0
Type :
conf
DOI :
10.1109/ICMCS.2014.6911160
Filename :
6911160
Link To Document :
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