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Issue No.05 - Sept.-Oct. (2013 vol.17)
pp: 46-53
Cristian Mateos , Argentinian National Council for Scientific and Technical Research
Marco Crasso , Argentinian National Council for Scientific and Technical Research
Alejandro Zunino , Argentinian National Council for Scientific and Technical Research
Jose Luis Ordiales Coscia , Universidad Nacional del Centro de la Provincia de Buenos Aires
In a previous article, the authors demonstrated that effectively discovering Web services helps developers avoid several common design errors in Web Service Description Language (WSDL) documents. Their proposed guidelines are unfortunately applicable only when publishers follow the top-down, or contract-first, method of building services, which isn't very popular due to its inherent costs. Here, they present an approach for preventing such errors when using a counterpart method--namely, bottom-up or code-first--and measure the approach's impact on service discovery. The rationale behind the study is that because code-first service interfaces are automatically generated by tools that--given a service implementation--deterministically map programming language constructs onto WSDL elements, the measurable properties of service implementations could influence resulting service interfaces.
Publishing, Web services, Data models, Information analysis, Documentation, Ports (Computers), Web Services Description Language, Electronic publishing,WSDL, Web services modeling, service architectures, Web Services Description Language, Web services publishing, services discovery process and methodology
Cristian Mateos, Marco Crasso, Alejandro Zunino, Jose Luis Ordiales Coscia, "Revising WSDL Documents: Why and How, Part 2", IEEE Internet Computing, vol.17, no. 5, pp. 46-53, Sept.-Oct. 2013, doi:10.1109/MIC.2013.4
1. M.N. Huhns and M.P. Singh, “Service-Oriented Computing: Key Concepts and Principles,” IEEE Internet Computing, vol. 9, no. 1, 2005, pp. 75-81.
2. P. Adamczyk et al., “Rest and Web Services: In Theory and in Practice,” REST: From Research to Practice, Springer, 2011, pp. 35-57.
3. J. Pasley, “Avoid XML Schema Wildcards for Web Service Interfaces,” IEEE Internet Computing, vol. 10, no. 3, 2006, pp. 72-79.
4. M.B. Blake and M.F. Nowlan, “Taming Web Services from the Wild,” IEEE Internet Computing, vol. 12, no. 5, 2008, pp. 62-69.
5. M. Crasso et al., “Revising WSDL documents: Why and How,” IEEE Internet Computing, vol. 14, no. 5, 2010, pp. 48-56.
6. J.M. Rodriguez et al., “Bottom-Up and Top-Down Cobol System Migration to Web Services: An Experience Report,” IEEE Internet Computing, vol. 17, no. 2, 2013, pp. 44-51.
7. M. Crasso, A. Zunino, and M. Campo, “A Survey of Approaches to Web Service Discovery in Service-Oriented Architectures,” J. Database Management, vol. 22, no. 1, 2011, pp. 103-134.
8. S. Chidamber and C. Kemerer, “A Metrics Suite for Object Oriented Design,” IEEE Trans. Software Eng., vol. 20, no. 6, 1994, pp. 476-493.
9. T. Gyimothy, R. Ferenc, and I. Siket, “Empirical Validation of Object-Oriented Metrics on Open Source Software for Fault Prediction,” IEEE Trans. Software Eng., vol. 31, no. 10, 2005, pp. 897-910.
10. C. Mateos et al., “Detecting WSDL Bad Practices in Code-First Web Services,” Int'l J. Web and Grid Services, vol. 7, no. 4, 2011, pp. 357-387.
11. D. Spinellis, “Tool Writing: A Forgotten Art?” IEEE Software, vol. 22, no. 4, 2005, pp. 9-11.
12. J.M. Rodriguez, M. Crasso, and A. Zunino, “An Approach for Web Service Discoverability Antipatterns Detection,” J. Web Eng., vol. 12, nos. 1 & 2, 2013, pp. 131-158.
13. M. Fowler et al., Refactoring: Improving the Design of Existing Code, Addison-Wesley Professional, 1999.
14. M. Crasso, A. Zunino, and M. Campo, “Combining Query-by-Example and Query Expansion for Simplifying Web Service Discovery,” Information Systems Frontiers, vol. 13, no. 3, 2011, pp. 407-428.
15. E. Agichtein et al., “Learning User Interaction Models for Predicting Web Search Result Preferences,” Proc. 29th Ann. Int'l ACM SIGIR Conf. Research and Development in Information Retrieval, ACM, 2006, pp. 3-10.
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