Control-Flow Residual Analysis for Symbolic Automata

TL;DR

This paper extends control-flow static analysis techniques to optimize symbolic automata, reducing runtime monitoring overheads in system correctness assurance, with empirical validation on a financial transaction system.

Contribution

It generalizes existing control-flow analysis methods to more expressive symbolic automata, enabling more efficient static analysis for system monitoring.

Findings

Significant reduction in monitoring overheads observed.

Effective application demonstrated on financial transaction system.

Analysis improves scalability of runtime verification.

Abstract

Where full static analysis of systems fails to scale up due to system size, dynamic monitoring has been increasingly used to ensure system correctness. The downside is, however, runtime overheads which are induced by the additional monitoring code instrumented. To address this issue, various approaches have been proposed in the literature to use static analysis in order to reduce monitoring overhead. In this paper we generalise existing work which uses control-flow static analysis to optimise properties specified as automata, and prove how similar analysis can be applied to more expressive symbolic automata - enabling reduction of monitoring instrumentation in the system, and also monitoring logic. We also present empirical evidence of the effectiveness of this approach through an analysis of the effect of monitoring overheads in a financial transaction system.