Nowadays, argumentation is a salient keyword in artificial intelligence. The use of argumentation techniques is particularly convenient for thematics such that multiagent systems, where it allows to describe dialog protocols (using persuasion, negotiation, ...) or on-line discussion analysis, it also allows to handle queries where a single agent has to reason with conflicting information (inference in the presence of inconsistency, inconsistency measure). This very rich framework gives numerous reasoning tools, thanks to several acceptability semantics and inference policies. On the other hand, the progress of SAT solvers in the recent years, and more generally the progress on Constraint Programming paradigms, lead to some powerful approaches that permit to tackle theoretically hard problems. The needs of efficient applications to solve the usual reasoning tasks in argumentation, together with the capabilities of modern Constraint Programming solvers, lead us to study the encoding of usual acceptability semantics into logical settings. We propose diverse use of Constraint Programming techniques to develop a software library dedicated to argumentative reasoning. We present a library which offers the advantages to be generic and easily adaptable. We finally describe an experimental study of our approach for a set of semantics and inference tasks, and we describe the behaviour of our solver during the First International Competition on Computational Models of Argumentation.