The precise computation of abstractions is a bottleneck in many approaches to CEGAR-based verification. In this paper, we propose a novel approach, based on the use of structural information. Rather than computing the abstraction as a single, monolithic quantification, we provide a \emph{structure-aware} abstraction algorithm, based on two complementary steps. The first, high-level step exploits the structure of the system, and partitions the abstraction problem into the combination of several smaller abstraction problems. This is represented as a formula with quantifiers. The second, low-level step exploits the structure of the formula, in particular the occurrence of variables within the quantifiers, and applies a set of low-level rewriting rules aiming at further reducing the scope of quantifiers. We experimentally evaluate the approach on a substantial set of benchmarks, and show significant speed ups compared to monolithic abstraction algorithms.

Structure-Aware Computation of Predicate Abstraction

Cimatti, Alessandro;Roveri, Marco
2009

Abstract

The precise computation of abstractions is a bottleneck in many approaches to CEGAR-based verification. In this paper, we propose a novel approach, based on the use of structural information. Rather than computing the abstraction as a single, monolithic quantification, we provide a \emph{structure-aware} abstraction algorithm, based on two complementary steps. The first, high-level step exploits the structure of the system, and partitions the abstraction problem into the combination of several smaller abstraction problems. This is represented as a formula with quantifiers. The second, low-level step exploits the structure of the formula, in particular the occurrence of variables within the quantifiers, and applies a set of low-level rewriting rules aiming at further reducing the scope of quantifiers. We experimentally evaluate the approach on a substantial set of benchmarks, and show significant speed ups compared to monolithic abstraction algorithms.
9781424449668
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/4980
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
social impact