Shaun Azzopardi

Shaun Azzopardi, Luca Di Stefano, Nir Piterman

Recent years have seen a significant increase in the interest in reactive synthesis from specifications that relate to infinite state spaces. We present sweap, a tool for synthesis of infinite-state Linear Integer Arithmetic reactive systems. sweap implements a CEGAR approach, relying on state-of-the-art finite-state synthesis tools as black boxes to solve abstract synthesis problems. sweap supports most common input formalisms for infinite-state reactive-synthesis problems: Temporal Stream Logic Modulo Theories, Reactive Program Games, the bespoke input of the ISSY tool, and our own bespoke input. We present a mature version of sweap with novel features: a dual abstraction approach that improves its capabilities in proving unrealisability, support for nondeterministic and unbounded updates, more general initialization of variables, and equirealisable reductions for optimisation. Experimental evaluation shows that sweap outperforms its only competitor in this domain.

Shaun Azzopardi, Christian Colombo, Gordon J. Pace

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.