Multi-Property Temporal Logic Monitoring
It addresses the scalability bottleneck of runtime verification for systems with dozens to hundreds of temporal properties, enabling efficient monitoring in high-performance and resource-constrained environments.
The paper presents a multi-property monitoring framework for temporal logic that compiles multiple specifications into a shared graph, achieving 2x-4.5x and 6x-12x per-property throughput improvements over single-property monitoring.
Runtime verification enables checking temporal logic specifications over individual execution traces and offers a scalable alternative to exhaustive formal verification. In practice, systems must satisfy dozens to hundreds of temporal properties simultaneously; however, existing approaches monitor each property in isolation, resulting in redundant computation and limited scalability. In this work, we present an online multi-property monitoring framework that compiles past-time LTL and MTL specifications into a shared directed acyclic graph of subformulas with one output per property. Unlike prior approaches that construct monitors independently, our method extends compositional sequential network-based temporal logic monitor construction to a shared setting, enabling reuse of intermediate results across properties while preserving their individual structure. Central to our approach is a data-oriented execution model based on an arena-allocated, double-buffered layout that stores intermediate results for each subformula in compact, contiguous memory. This design favors spatial locality and enables incremental updates with minimal overhead. Experimental results demonstrate per-property throughput improvements of 2x to 4.5x and 6x to 12x in multi-property configurations compared to conventional single-property monitoring, enabling scalability to large specification sets and deployment in high-performance and resource-constrained systems.