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Such derived \nfeatures and constraints are frequently defined by \ndeclarative techniques (such graph patterns or OCL \ninvariants). However, for complex domains, derived features \nand constraints can easily be formalized incorrectly \nresulting in inconsistent, incomplete or ambiguous DSL \nspecifications. To detect such issues, we propose an \nautomated mapping of EMF metamodels enriched with derived \nfeatures and well-formedness constraints captured as graph \nqueries in EMF-IncQuery or (a subset of) OCL invariants into \nan effectively propositional fragment of first-order logic \nwhich can be efficiently analyzed by back-end reasoners. On \nthe conceptual level, the main added value of our encoding is \n(1) to transform graph patterns of the EMF-IncQuery framework \ninto FOL and (2) to introduce approximations for complex \nlanguage features (e.g., transitive closure or \nmultiplicities) which are not expressible in FOL. On the \npractical level, we identify and address relevant challenges \nand scenarios for systematically validating DSL \nspecifications. Our approach is supported by a tool, and it \nwill be illustrated on analyzing a DSL in the avionics \ndomain. 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