Table of Contents
ISRN Software Engineering
Volume 2013 (2013), Article ID 408267, 26 pages
Research Article

Web Services Conversation Adaptation Using Conditional Substitution Semantics of Application Domain Concepts

Computer Engineering Department, Middle East Technical University, Northern Cyprus Campus, Guzelyurt, Mersin 10, Turkey

Received 5 June 2013; Accepted 12 July 2013

Academic Editors: A. Lastovetsky, G. Petrone, and G. Saake

Copyright © 2013 Islam Elgedawy. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Internet of Services (IoS) vision allows users to allocate and consume different web services on the fly without any prior knowledge regarding the chosen services. Such chosen services should automatically interact with one another in a transparent manner to accomplish the required users' goals. As services are chosen on the fly, service conversations are not necessarily compatible due to incompatibilities between services signatures and/or conversation protocols, creating obstacles for realizing the IoS vision. One approach for overcoming this problem is to use conversation adapters. However, such conversion adapters must be automatically created on the fly as chosen services are only known at run time. Existing approaches for automatic adapter generation are syntactic and very limited; hence they cannot be adopted in such dynamic environments. To overcome such limitation, this paper proposes a novel approach for automatic adapter generation that uses conditional substitution semantics between application domain concepts and operations to automatically generate the adapter conversion functions. Such conditional substitution semantics are captured using a concepts substitutability enhanced graph required to be part of application domain ontologies. Experiments results show that the proposed approach provides more accurate conversation adaptation results when compared against existing syntactic adapter generation approaches.