Linear-Time Verification of Data-Aware Dynamic Systems with Arithmetic

Combined modeling and verification of dynamic systems the data they operate on has gained momentum in AI several application domains. We investigate expressive yet concise framework data-aware (DDS), extending it with linear arithmetic, providing following contributions. First, we introduce a new, semantic property “finite summary”, which guarantees existence faithful finite-state abstraction. rely this to show that checking whether witness exists for linear-time, finite-trace is decidable DDSs finite summary. Second, demonstrate decidability conditions studied formal methods database theory can be seen as concrete, checkable instances property. This also gives rise new results. Third, how abstract, uniform summary leads modularity results: system enjoys if partitioned appropriately into smaller possess Our results allow us analyze were out reach earlier approaches. Finally, feasibility our approach prototype implementation.