Multi-Property Temporal Logic Monitoring

2026-05-13

AI Summary

Existing runtime verification approaches monitor each temporal property in isolation, leading to computational redundancy and poor scalability. This work proposes the first online monitoring framework that supports multi-property sharing by compiling past-time LTL/MTL specifications into a directed acyclic graph of shared subformulas, enabling reuse of intermediate results across properties. It innovatively extends compositional sequential network monitoring to the multi-property setting and introduces a data-oriented execution model based on arena allocation and double buffering, significantly improving memory locality and incremental update efficiency. Experimental results demonstrate throughput improvements of 2–4.5× for single-property monitoring and 6–12× in multi-property configurations, substantially enhancing the deployability of large specification sets on both high-performance and resource-constrained systems.

Abstract

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.

Problem

• runtime verification
• temporal logic monitoring
• multi-property
• scalability
• redundant computation

Innovation

• multi-property monitoring
• shared DAG
• compositional monitoring
• data-oriented execution
• temporal logic