In recent times, satisfiability modulo theories (SMT) techniques gained increasing attention and obtained remarkable success in model-checking infinite-state systems. Still, we believe that whenever more expressivity is needed in order to specify the systems to be verified, more and more support is needed from mathematical logic and model theory. This is the case of the applications considered in this paper: we study verification over a general model of relational, data-aware processes, to assess (parameterized) safety properties irrespectively of the initial database (DB) instance. Toward this goal, we take inspiration from array-based systems and tackle safety algorithmically via backward reachability. To enable the adoption of this technique in our rich setting, we make use of the model-theoretic machinery of model completion, which surprisingly turns out to be an effective tool for verification of relational systems and represents the main original contribution of this paper. In this way, we pursue a twofold purpose. On the one hand, we isolate three notable classes for which backward reachability terminates, in turn witnessing decidability. Two of such classes relate our approach to conditions singled out in the literature, whereas the third one is genuinely novel. On the other hand, we are able to exploit SMT technology in implementations, building on the well-known MCMT (Model Checker Modulo Theories) model checker for array-based systems and extending it to make all our foundational results fully operational. All in all, the present contribution is deeply rooted in the long-standing tradition of the application of model theory in computer science. In particular, this paper applies these ideas in an original mathematical context and shows how these techniques can be used for the first time to empower algorithmic techniques for the verification of infinite-state systems based on arrays, so as to make such techniques applicable to the timely, challenging settings of data-aware processes.

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We propose DAB -a data-aware extension of BPMN where the process operates over case and persistent data (partitioned into a read-only database called catalog and a read-write database called repository). The model trades off between expressiveness and the possibility of supporting parameterized verification of safety properties on top of it. Specifically, taking inspiration from the literature on verification of artifact systems, we study verification problems where safety properties are checked irrespectively of the content of the read-only catalog, and accepting the potential presence of unboundedly many tuples in the catalog and repository. We tackle such problems using an array-based backward reachability procedure fully implemented in MCMT -a state-of-the-art arraybased SMT model checker. Notably, we prove that the procedure is sound and complete for checking safety of DABs, and single out additional conditions that guarantee its termination and, in turn, show decidability of checking safety.

We study verification over a general model of artifact-centric systems, to assess (parameterized) safety properties irrespectively of the initial database instance. We view such artifact systems as array-based systems, which allows us to check safety by adapting backward reachability, establishing for the first time a correspondence with model checking based on Satisfiability-Modulo-Theories (SMT). To do so, we make use of the modeltheoretic machinery of model completion, which surprisingly turns out to be an effective tool for verification of relational systems, and represents the main original contribution of this paper. In this way, we pursue a twofold purpose. On the one hand, we reconstruct (restricted to safety) the essence of some important decidability results obtained in the literature for artifact-centric systems, and we devise a genuinely novel class of decidable cases. On the other, we are able to exploit SMT technology in implementations, building on the well-known MCMT model checker for array-based systems, and extending it to make all our foundational results fully operational.

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