<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">José Proença</style></author><author><style face="normal" font="default" size="100%">Dave Clarke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Data Abstraction in Coordination Constraints</style></title><secondary-title><style face="normal" font="default" size="100%">Advances in Service-Oriented and Cloud Computing - Workshops - ESOCC </style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">September</style></date></pub-dates></dates><urls><related-urls><url><style face="normal" font="default" size="100%">https://haslab.uminho.pt/sites/default/files/joseproenca/files/data-abstraction.pdf</style></url></related-urls></urls><pub-location><style face="normal" font="default" size="100%">Málaga, Spain</style></pub-location><pages><style face="normal" font="default" size="100%">159–173</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This paper studies complex coordination mechanisms based on constraint satisfaction. In particular, it focuses on data-sensitive connectors from the Reo coordination language. These connectors restrict how and where data can flow between loosely-coupled components taking into account the data being exchanged. Existing engines for Reo provide a very limited support for data-sensitive connectors, even though data constraints are captured by the original semantic models for Reo. When executing data-sensitive connectors, coordination constraints are not exhaustively solved at compile time but at runtime on a per-need basis, powered by an existing SMT (satisfiability modulo theories) solver.To deal with a wider range of data types and operations, we abstract data and reduce the original constraint satisfaction problem to a SAT problem, based on a variation of predicate abstraction. We show soundness and completeness of the abstraction mechanism for well-defined constraints, and validate our approach by evaluating the performance of a prototype implementation with different test cases, with and without abstraction.&lt;/p&gt;
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