Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/52697
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dc.contributor.authorYu, J.-
dc.contributor.authorHan, Y.-
dc.contributor.authorHan, J.-
dc.contributor.authorJin, Y.-
dc.contributor.authorFalcarin, P.-
dc.contributor.authorMorisio, M.-
dc.date.issued2008-
dc.identifier.citationJournal of Computer Science and Technology, 2008; 23(6):885-894-
dc.identifier.issn1000-9000-
dc.identifier.issn1860-4749-
dc.identifier.urihttp://hdl.handle.net/2440/52697-
dc.description.abstractTransformational approaches to generating design and implementation models from requirements can bring effectiveness and quality to software development. In this paper we present a framework and associated techniques to generate the process model of a service composition from a set of temporal business rules. Dedicated techniques including path-finding, branching structure identification and parallel structure identification are used for semi-automatically synthesizing the process model from the semantics-equivalent Finite State Automata of the rules. These process models naturally satisfy the prescribed behavioral constraints of the rules. With the domain knowledge encoded in the temporal business rules, an executable service composition program, e.g., a BPEL program, can be further generated from the process models. A running example in the e-business domain is used for illustrating our approach throughout this paper. Electronic supplementary material The online version of this article (doi: 10.1007/s11390-008-9196-x) contains supplementary material, which is available to authorized users.-
dc.description.statementofresponsibilityJian Yu, Yan-Bo Han, Jun Han, Yan Jin, Paolo Falcarin and Maurizio Morisio-
dc.language.isoen-
dc.publisherSpringer New York LLC-
dc.subjectservice composition-
dc.subjectcomposition synthesis-
dc.subjectbehavioral model-
dc.subjecttemporal patterns-
dc.titleSynthesizing Service Composition Models on the Basis of Temporal Business Rules-
dc.typeJournal article-
dc.identifier.doi10.1007/s11390-008-9196-x-
dc.relation.granthttp://purl.org/au-research/grants/arc/LP0775188-
pubs.publication-statusPublished-
Appears in Collections:Aurora harvest
Computer Science publications

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