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Notice of Violation of IEEE Publication Principles: Applying Formal Methods to Compositionality Description of Web Service

Authors: HuaiKou Miao; JunFeng Wu;

Notice of Violation of IEEE Publication Principles: Applying Formal Methods to Compositionality Description of Web Service

Abstract

Web services are a relatively new paradigm for building distributed Web applications. Normally for proving properties of service compositions, and mapping the pre/post-conditions are assertions only on the initial and final states of the service respectively. They do not help in specifying and verifying ongoing behavior of a composite Web service system. We propose a formal framework for enriching composite service description with two additional assertions: assumption and commitment that facilitate compositional reasoning about services for the composition of their integration. The technique is based on Maude language, a rewriting logic based methodology in which formal modeling and analysis can be used from the earliest phases of system design to uncover many errors and inconsistencies, and to reach high assurance for critical components with runtime verification.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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