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Program Verification using Constraint Handling Rules and Array Constraint Generalizations

De Angelis E., Fioravanti F., Pettorossi A., Proietti M.

Fundamenta Informaticae

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2017

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Vol. 150, nr 1

73--117

EN

The transformation of constraint logic programs (CLP programs) has been shown to be an effective methodology for verifying properties of imperative programs. By following this methodology, we encode the negation of a partial correctness property of an imperative program prog as a predicate incorrect defined by a CLP program T, and we show that prog is correct by transforming T into the empty program (and thus incorrect does not hold) through the application of semantics preserving transformation rules. We can also show that prog is incorrect by transforming T into a program with the fact incorrect (and thus incorrect does hold). Some of the transformation rules perform replacements of constraints that are based on properties of the data structures manipulated by the program prog. In this paper we show that Constraint Handling Rules (CHR) are a suitable formalism for representing and applying constraint replacements during the transformation of CLP programs. In particular, we consider programs that manipulate integer arrays and we present a CHR encoding of a constraint replacement strategy based on the theory of arrays. We also propose a novel generalization strategy for constraints on integer arrays that combines CHR constraint replacements with various generalization operators on integer constraints, such as widening and convex hull. Generalization is controlled by additional constraints that relate the variable identifiers in the imperative program prog and the CLP representation of their values. The method presented in this paper has been implemented and we have demonstrated its effectiveness on a set of benchmark programs taken from the literature.

2

A Rule-based Verification Strategy for Array Manipulating Programs

De Angelis E., Fioravanti F., Pettorossi A., Proietti M.

Fundamenta Informaticae

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2015

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Vol. 140, nr 3/4

329--355

EN

We present a method for verifying properties of imperative programs that manipulate integer arrays. Imperative programs and their properties are represented by using Constraint Logic Programs (CLP) over integer arrays. Our method is refutational. Given a Hoare triple {ϕ} prog {ψ} that defines a partial correctness property of an imperative program prog, we encode the negation of the property as a predicate incorrect defined by a CLP program P, and we show that the property holds by proving that incorrect is not a consequence of P. Program verification is performed by applying a sequence of semantics preserving transformation rules and deriving a new CLP program T such that incorrect is a consequence of P iff it is a consequence of T . The rules are applied according to an automatic strategy whose objective is to derive a program T that satisfies one of the following properties: either (i) T is the empty set of clauses, hence proving that incorrect does not hold and prog is correct, or (ii) T contains the fact incorrect, hence proving that prog is incorrect. Our transformation strategy makes use of an axiomatization of the theory of arrays for the manipulation of array constraints, and also applies the widening and convex hull operators for the generalization of linear integer constraints. The strategy has been implemented in the VeriMAP transformation system and it has been shown to be quite effective and efficient on a set of benchmark array programs taken from the literature.

3

Synthesizing Concurrent Programs Using Answer Set Programming

De Angelis E., Pettorossi A., Proietti M.

Fundamenta Informaticae

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2012

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Vol. 120, nr 3/4

205-229

EN

We address the problem of the automatic synthesis of concurrent programs within a framework based on Answer Set Programming (ASP). Every concurrent program to be synthesized is specified by providing both the behavioural and the structural properties it should satisfy. Behavioural properties, such as safety and liveness properties, are specified by using formulas of the Computation Tree Logic, which are encoded as a logic program. Structural properties, such as the symmetry of processes, are also encoded as a logic program. Then, the program which is the union of these two encoding programs, is given as input to an ASP system which returns as output a set of answer sets. Finally, each answer set is decoded into a synthesized program that, by construction, satisfies the desired behavioural and structural properties.