Data Flow Analysis of Asynchronous Systems using Infinite Abstract Domains

TL;DR

This paper introduces an advanced data flow analysis method for asynchronous systems that uses infinite abstract domains to improve precision by effectively skipping infeasible execution paths.

Contribution

It generalizes existing finite domain approaches to include infinite domains, enabling higher precision in analyzing asynchronous message-passing systems.

Findings

Significantly higher analysis precision on benchmarks

Effective skipping of infeasible paths

Implementation demonstrates practical feasibility

Abstract

Asynchronous message-passing systems are employed frequently to implement distributed mechanisms, protocols, and processes. This paper addresses the problem of precise data flow analysis for such systems. To obtain good precision, data flow analysis needs to somehow skip execution paths that read more messages than the number of messages sent so far in the path, as such paths are infeasible at run time. Existing data flow analysis techniques do elide a subset of such infeasible paths, but have the restriction that they admit only finite abstract analysis domains. In this paper we propose a generalization of these approaches to admit infinite abstract analysis domains, as such domains are commonly used in practice to obtain high precision. We have implemented our approach, and have analyzed its performance on a set of 14 benchmarks. On these benchmarks our tool obtains significantly higher precision compared to a baseline approach that does not elide any infeasible paths and to another baseline that elides infeasible paths but admits only finite abstract domains.