582 research outputs found
Invariant Synthesis for Incomplete Verification Engines
We propose a framework for synthesizing inductive invariants for incomplete
verification engines, which soundly reduce logical problems in undecidable
theories to decidable theories. Our framework is based on the counter-example
guided inductive synthesis principle (CEGIS) and allows verification engines to
communicate non-provability information to guide invariant synthesis. We show
precisely how the verification engine can compute such non-provability
information and how to build effective learning algorithms when invariants are
expressed as Boolean combinations of a fixed set of predicates. Moreover, we
evaluate our framework in two verification settings, one in which verification
engines need to handle quantified formulas and one in which verification
engines have to reason about heap properties expressed in an expressive but
undecidable separation logic. Our experiments show that our invariant synthesis
framework based on non-provability information can both effectively synthesize
inductive invariants and adequately strengthen contracts across a large suite
of programs
Invariant Synthesis for Incomplete Verification Engines
We propose a framework for synthesizing inductive invariants for incomplete verification engines, which soundly reduce logical problems in undecidable theories to decidable theories. Our framework is based on the counter-example guided inductive synthesis principle (CEGIS) and allows verification engines to communicate non-provability information to guide invariant synthesis. We show precisely how the verification engine can compute such non-provability information and how to build effective learning algorithms when invariants are expressed as Boolean combinations of a fixed set of predicates. Moreover, we evaluate our framework in two verification settings, one in which verification engines need to handle quantified formulas and one in which verification engines have to reason about heap properties expressed in an expressive but undecidable separation logic. Our experiments show that our invariant synthesis framework based on non-provability information can both effectively synthesize inductive invariants and adequately strengthen contracts across a large suite of programs
Compositional Computational Reflection
Current work on computational reflection is single-minded; each reflective procedure is written with a specific application or scope in mind. Composition of these reflective procedures is done by a proof- generating tactic language such as Ltac. This composition, however, comes at the cost of both larger proof terms and redundant preprocessing. In this work, we propose a methodology for writing composable reflective procedures that solve many small tasks in a single invocation. The key technical insights are techniques for reasoning semantically about extensible syntax in intensional type theory. Our techniques make it possible to compose sound procedures and write generic procedures parametrized by lemmas mimicking Coq’s support for hint databases.Engineering and Applied Science
Predicate Abstraction for Linked Data Structures
We present Alias Refinement Types (ART), a new approach to the verification
of correctness properties of linked data structures. While there are many
techniques for checking that a heap-manipulating program adheres to its
specification, they often require that the programmer annotate the behavior of
each procedure, for example, in the form of loop invariants and pre- and
post-conditions. Predicate abstraction would be an attractive abstract domain
for performing invariant inference, existing techniques are not able to reason
about the heap with enough precision to verify functional properties of data
structure manipulating programs. In this paper, we propose a technique that
lifts predicate abstraction to the heap by factoring the analysis of data
structures into two orthogonal components: (1) Alias Types, which reason about
the physical shape of heap structures, and (2) Refinement Types, which use
simple predicates from an SMT decidable theory to capture the logical or
semantic properties of the structures. We prove ART sound by translating types
into separation logic assertions, thus translating typing derivations in ART
into separation logic proofs. We evaluate ART by implementing a tool that
performs type inference for an imperative language, and empirically show, using
a suite of data-structure benchmarks, that ART requires only 21% of the
annotations needed by other state-of-the-art verification techniques
The Effects of Adding Reachability Predicates in Propositional Separation Logic
International audienceThe list segment predicate ls used in separation logic for verifying programs with pointers is well-suited to express properties on singly-linked lists. We study the effects of adding ls to the full proposi-tional separation logic with the separating conjunction and implication, which is motivated by the recent design of new fragments in which all these ingredients are used indifferently and verification tools start to handle the magic wand connective. This is a very natural extension that has not been studied so far. We show that the restriction without the separating implication can be solved in polynomial space by using an appropriate abstraction for memory states whereas the full extension is shown undecidable by reduction from first-order separation logic. Many variants of the logic and fragments are also investigated from the computational point of view when ls is added, providing numerous results about adding reachability predicates to propositional separation logic
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The distributed computer system
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University
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