A simple abstraction of arrays and maps by program translation

We present an approach for the static analysis of programs handling arrays, with a Galois connection between the semantics of the array program and semantics of purely scalar operations. The simplest way to implement it is by automatic, syntactic transformation of the array program into a scalar program followed analysis of the scalar program with any static analysis technique (abstract interpretation, acceleration, predicate abstraction,.. .). The scalars invariants thus obtained are translated back onto the original program as universally quantified array invariants. We illustrate our approach on a variety of examples, leading to the " Dutch flag " algorithm

Cell morphing: from array programs to array-free Horn clauses

International audienceAutomatically verifying safety properties of programs is hard.Many approaches exist for verifying programs operating on Boolean and integer values (e.g. abstract interpretation, counterexample-guided abstraction refinement using interpolants), but transposing them to array properties has been fraught with difficulties.Our work addresses that issue with a powerful and flexible abstractionthat morphes concrete array cells into a finite set of abstractones. This abstraction is parametric both in precision and in theback-end analysis used.From our programs with arrays, we generate nonlinear Horn clauses overscalar variables only, in a common format with clear and unambiguouslogical semantics, for which there exist several solvers. We thusavoid the use of solvers operating over arrays, which are still veryimmature.Experiments with our prototype VAPHOR show that this approach can proveautomatically and without user annotationsthe functional correctness of several classical examples, including \emph{selection sort}, \emph{bubble sort}, \emph{insertion sort}, as well as examples from literature on array analysis

Proving array properties using data abstraction

International audienceThis paper presents a framework to abstract data structures within Horn clauses that allows abstractions to be easily expressed, compared, composed and implemented. These abstractions introduce new quantifiers that we eliminate with quantifier elimination techniques. Experimental evaluation show promising results on classical array programs

Computer Aided Verification

This open access two-volume set LNCS 11561 and 11562 constitutes the refereed proceedings of the 31st International Conference on Computer Aided Verification, CAV 2019, held in New York City, USA, in July 2019. The 52 full papers presented together with 13 tool papers and 2 case studies, were carefully reviewed and selected from 258 submissions. The papers were organized in the following topical sections: Part I: automata and timed systems; security and hyperproperties; synthesis; model checking; cyber-physical systems and machine learning; probabilistic systems, runtime techniques; dynamical, hybrid, and reactive systems; Part II: logics, decision procedures; and solvers; numerical programs; verification; distributed systems and networks; verification and invariants; and concurrency