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Let $\mathcal{L}_{\mathcal{X}}$ be the language of first-order, decidable theory $\mathcal{X}$. Consider the language, $\mathcal{L}_{\mathcal{RQ}}(\mathcal{X})$, that extends $\mathcal{L}_{\mathcal{X}}$ with formulas of the form $\forall x \in A: \phi$ (restricted universal quantifier, RUQ) and $\exists x \in A: \phi$ (restricted existential quantifier, REQ), where $A$ is a finite set and $\phi$ is a formula made of $\mathcal{X}$-formulas, RUQ and REQ. That is, $\mathcal{L}_{\mathcal{RQ}}(\mathcal{X})$ admits nested restricted quantifiers. In this paper we present a decision procedure for $\mathcal{L}_{\mathcal{RQ}}(\mathcal{X})$ based on the decision procedure already defined for the Boolean algebra of finite sets extended with restricted intensional sets ($\mathcal{L}_\mathcal{RIS}$). The implementation of the decision procedure as part of the $\{log\}$ (`setlog') tool is also introduced. The usefulness of the approach is shown through a number of examples drawn from several real-world case studies.

In this paper we show how prescritive type checking and constraint solving can be combined to increase automation during software verification. We do so by defining a type system and implementing a typechecker for {log} (read `setlog'), a Constraint Logic Programming (CLP) language and satisfiability solver based on set theory. Hence, we proceed as follows: a) a type system for {log} is defined; b) the constraint solver is proved to be safe w.r.t. the type system; c) the implementation of a concrete typechecker is presented; d) the integration of type checking and set constraint solving to increase automation during software verification is discussed; and f) two industrial-strength case studies are presented where this combination is used with very good results. Under consideration in Theory and Practice of Logic Programming (TPLP), Comment: Under consideration in Theory and Practice of Logic Programming (TPLP)

In this paper we show how $\{log\}$ (read `setlog'), a Constraint Logic Programming (CLP) language based on set theory, can be used as an automated verifier for B specifications. In particular we encode in $\{log\}$ an Event-B specification, developed by Mammar and Laleau, of the case study known as the Landing Gear System (LGS). Next we use $\{log\}$ to discharge all the proof obligations proposed in the Event-B specification by the Rodin platform. In this way, the $\{log\}$ program can be regarded as an automatically verified prototype of the LGS. We believe this case study provides empirical evidence on how CLP and set theory can be used in tandem as a vehicle for program verification.

In this paper we extend a decision procedure for the Boolean algebra of finite sets with cardinality constraints ($\mathcal{L}_{\lvert\cdot\rvert}$) to a decision procedure for $\mathcal{L}_{\lvert\cdot\rvert}$ extended with set terms denoting finite integer intervals ($\mathcal{L}_{[\,]}$). In $\mathcal{L}_{[\,]}$ interval limits can be integer linear terms including \emph{unbounded variables}. These intervals are a useful extension because they allow to express non-trivial set operators such as the minimum and maximum of a set, still in a quantifier-free logic. Hence, by providing a decision procedure for $\mathcal{L}_{[\,]}$ it is possible to automatically reason about a new class of quantifier-free formulas. The decision procedure is implemented as part of the $\{log\}$ tool. The paper includes a case study based on the elevator algorithm showing that $\{log\}$ can automatically discharge all its invariance lemmas some of which involve intervals., Comment: arXiv admin note: text overlap with arXiv:2102.05422

$\{log\}$ is a programming language at the intersection of Constraint Logic Programming, set programming and declarative programming. But $\{log\}$ is also a satisfiability solver for a theory of finite sets and finite binary relations. With $\{log\}$ programmers can write abstract programs using all the power of set theory and binary relations. These programs are not very efficient but they are very close to specifications. Then, their correctness is more evident. Furthermore, $\{log\}$ programs are also set formulas. Hence, programmers can use $\{log\}$ again to automatically prove their programs verify non trivial properties. In this paper we show this development methodology by means of several examples.

This document shows how Z specifications can be translated into $\{log\}$ and, later, on how $\{log\}$ can be used to run simulations and automated proofs. This can help users of other specification languages such as B and VDM to use $\{log\}$ along the same lines. The presentation is rather informal and user-oriented. More technical and formal presentations can be found in the papers published by the authors. We also assume the reader has at least a basic knowledge of the Z notation.

Formal reasoning about finite sets and cardinality is an important tool for many applications, including software verification, where very often one needs to reason about the size of a given data structure and not only about what its elements are. The Constraint Logic Programming tool {log} provides a decision procedure for deciding the satisfiability of formulas involving very general forms of finite sets, without cardinality. In this paper we adapt and integrate a decision procedure for a theory of finite sets with cardinality into {log}. The proposed solver is proved to be a decision procedure for its formulas. Besides, the new CLP instance is implemented as part of the {log} tool. In turn, the implementation uses Howe and King's Prolog SAT solver and Prolog's CLP(Q) library, as an integer linear programming solver. The empirical evaluation of this implementation based on +250 real verification conditions shows that it can be useful in practice., Comment: Under consideration in Theory and Practice of Logic Programming (TPLP)

{log} ('setlog') is a satisfiability solver for formulas of the theory of finite sets and finite set relation algebra (FSTRA). As such, it can be used as an automated theorem prover (ATP) for this theory. {log} is able to automatically prove a number of FSTRA theorems, but not all of them. Nevertheless, we have observed that many theorems that {log} cannot automatically prove can be divided into a few subgoals automatically dischargeable by {log}. The purpose of this work is to present a prototype interactive theorem prover (ITP), called {log}-ITP, providing evidence that a proper integration of {log} into world-class ITP's can deliver a great deal of proof automation concerning FSTRA. An empirical evaluation based on 210 theorems from the TPTP and Coq's SSReflect libraries shows a noticeable reduction in the size and complexity of the proofs with respect to Coq.

Intensional sets, i.e., sets given by a property rather than by enumerating elements, are widely recognized as a key feature to describe complex problems (see, e.g., specification languages such as B and Z). Notwithstanding, very few tools exist supporting high-level automated reasoning on general formulas involving intensional sets. In this paper we present a decision procedure for a first-order logic language offering both extensional and (a restricted form of) intensional sets (RIS). RIS are introduced as first-class citizens of the language and set-theoretical operators on RIS are dealt with as constraints. Syntactic restrictions on RIS guarantee that the denoted sets are finite, though unbounded. The language of RIS, called L_RIS , is parametric with respect to any first-order theory X providing at least equality and a decision procedure for X-formulas. In particular, we consider the instance of L_RIS when X is the theory of hereditarily finite sets and binary relations. We also present a working implementation of this instance as part of the {log} tool and we show through a number of examples and two case studies that, although RIS are a subclass of general intensional sets, they are still sufficiently expressive as to encode and solve many interesting problems. Finally, an extensive empirical evaluation provides evidence that the tool can be used in practice.

Lists, multisets, and sets are well-known data structures whose usefulness is widely recognized in various areas of Computer Science. These data structures have been analyzed from an axiomatic point of view with a parametric approach in (*) where the relevant unification algorithms have been developed. In this paper we extend these results considering more general constraints including not only equality but also membership constraints as well as their negative counterparts. (*) A. Dovier, A. Policriti, and G. Rossi. A uniform axiomatic view of lists, multisets, and sets, and the relevant unification algorithms. Fundamenta Informaticae, 36(2/3):201--234, 1998., Comment: 27 pages, 11 figures

The unification problem in algebras capable of describing sets has been tackled, directly or indirectly, by many researchers and it finds important applications in various research areas--e.g., deductive databases, theorem proving, static analysis, rapid software prototyping. The various solutions proposed are spread across a large literature. In this paper we provide a uniform presentation of unification of sets, formalizing it at the level of set theory. We address the problem of deciding existence of solutions at an abstract level. This provides also the ability to classify different types of set unification problems. Unification algorithms are uniformly proposed to solve the unification problem in each of such classes. The algorithms presented are partly drawn from the literature--and properly revisited and analyzed--and partly novel proposals. In particular, we present a new goal-driven algorithm for general ACI1 unification and a new simpler algorithm for general (Ab)(Cl) unification., Comment: 58 pages, 9 figures, 1 table. To appear in Theory and Practice of Logic Programming (TPLP)