Property Refinement in Linear Temporal Logic: Formal Semantics and Algorithms for Software Verification

Model checking using temporal logic is a key aspect of formal verification of modern complex software systems. These systems are often the result of distributed development processes, involving multiple teams and iterative design cycles. This complexity is mirrored in the corresponding formal specifications, which often consist of a large number of temporal logic properties that need to be verified against a system model. Many of these properties overlap semantically, yet traditional verification treats them as independent, resulting in redundant checks that waste computational resources and inflate engineering effort. We address this by introducing and operationalizing a formal theory of property refinement for temporal logic into a concrete methodology that automatically identifies redundant properties from a verification suite. This is achieved by first partitioning specifications into equivalence classes based on shared atomic propositions, followed by an analysis of intra-class refinement relations to construct the minimal sufficient subset. Our extensive empirical evaluation confirms the practical viability of our approach, demonstrating it can reduce the number of required verification tasks by up to 75% and accelerate model checking by up to three orders of magnitude, with a one-time associated overhead cost of 0.035% for the refinement analysis. The results of the evaluation confirm that the benefits of this approach are threefold: it reduces the computational requirements for formal verification; it allows engineers to focus on the core requirements of the system, hereby reducing engineering effort; finally, the one-time negligible investment in refinement yields compounding returns, making it particularly advantageous for agile and long-term development lifecycles. This work thus establishes property refinement analysis as a key technique for scaling requirement engineering and software verification to modern complex software systems.