Abstract

Formalisms based on temporal logics interpreted over finite strict linear orders, known in the literature as finite traces , have been used for temporal specification in automated planning, process modelling, (runtime) verification and synthesis of programs, as well as in knowledge representation and reasoning. In this paper, we focus on first-order temporal logic on finite traces . We first investigate preservation of equivalences and satisfiability of formulas between finite and infinite traces, by providing a set of semantic and syntactic conditions to guarantee when the distinction between reasoning in the two cases can be blurred. Moreover, we show that the satisfiability problem on finite traces for several decidable fragments of first-order temporal logic is ExpSpace -complete, as in the infinite trace case, while it decreases to NExpTime when finite traces bounded in the number of instants are considered. This leads also to new complexity results for temporal description logics over finite traces. Finally, we investigate applications to planning and verification, in particular by establishing connections with the notions of insensitivity to infiniteness and safety from the literature. Linear temporal logic over finite traces is used as a formalism for temporal specification in automated planning, process modelling and (runtime) verification. In this paper, we investigate first-order temporal logic over finite traces, lifting some known results to a more expressive setting. Satisfiability in the two-variable monodic fragment is shown to be ExpSpace -complete, as for the infinite trace case, while it decreases to NExpTime when we consider finite traces bounded in the number of instants. This leads to new complexity results for temporal description logics over finite traces. We further investigate satisfiability and equivalences of formulas under a model-theoretic perspective, providing a set of semantic conditions that characterise when the distinction between reasoning over finite and infinite traces can be blurred. Finally, we apply these conditions to planning and verification.

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