SMT solvers are efficient tools to decide the satisfiability of ground formulas, including a number of built-in theories such as congruence, linear arithmetic, arrays, and bit-vectors. Adding a theory to that list requires delving into the implementation details of a given SMT solver, and is done mainly by the developers of the solver itself. For many useful theories, one can alternatively provide a first-order axiomatization. However, in the presence of quantifiers, SMT solvers are incomplete and exhibit unpredictable behavior. Consequently, this approach can not provide us with a complete and terminating treatment of the theory of interest. In this paper, we propose a framework to solve this problem, based on the notion of instantiation patterns, also known as triggers. Triggers are annotations that suggest instances which are more likely to be useful in proof search. They are implemented in all SMT solvers that handle first-order logic and are included in the SMT-LIB format. In our framework, the user provides a theory axiomatization with triggers, along with a proof of completeness and termination properties of this axiomatization, and obtains a sound, complete, and terminating solver for her theory in return. We describe and prove a corresponding extension of the traditional Abstract DPLL Modulo Theory framework. Implementing this mechanism in a given SMT solver requires a one-time development effort. We believe that this effort is not greater than that of adding a single decision procedure to the same SMT solver. We have implemented the proposed extension in the Alt-Ergo prover and we discuss some implementation details in the paper. To show that our framework can handle complex theories, we prove completeness and termination of a feature-rich axiomatization of doubly-linked lists. Our tests show that our approach results in a better performance of the solver on goals that stem from the verification of programs manipulating doubly-linked lists.

Verification of safety properties of concurrent programs with an arbitrary numbers of processes is an old challenge. In particular, complex parameterized protocols like FLASH are still out of the scope of state-of-the-art model checkers. In this paper, we describe a new algorithm, called Brab, that is able to automatically infer invariants strong enough to prove a protocol like FLASH. Brab computes over-approximations of backward reachable states that are checked to be unreachable in a finite instance of the system. These approximations (candidate invariants) are then model checked together with the original safety properties. Completeness of the approach is ensured by a mechanism for backtracking on spurious traces introduced by too coarse approximations.

SMT solvers are efficient tools to decide the satisfiability of ground formulas, including a number of built-in theories such as congruence, linear arithmetic, arrays, and bit-vectors. Adding a theory to that list requires delving into the implementation details of a given SMT solver, and is done mainly by the developers of the solver itself. For many useful theories, one can alternatively provide a first-order axiomatization. However, in the presence of quantifiers, SMT solvers are incomplete and exhibit unpredictable behavior. Consequently, this approach can not provide us with a complete and terminating treatment of the theory of interest. In this paper, we propose a framework to solve this problem, based on the notion of instantiation patterns, also known as triggers. Triggers are annotations that suggest instances which are more likely to be useful in proof search. They are implemented in all SMT solvers that handle first-order logic and are included in the SMT-LIB format. In our framework, the user provides a theory axiomatization with triggers, along with a proof of completeness and termination properties of this axiomatization, and obtains a sound, complete, and terminating solver for her theory in return. We describe and prove a corresponding extension of the traditional Abstract DPLL Modulo Theory framework. Implementing this mechanism in a given SMT solver requires a one-time development effort. We believe that this effort is not greater than that of adding a single decision procedure to the same SMT solver. We have implemented the proposed extension in the Alt-Ergo prover and we discuss some implementation details in the paper. To show that our framework can handle complex theories, we prove completeness and termination of a feature-rich axiomatization of doubly-linked lists. Our tests show that our approach results in a better performance of the solver on goals that stem from the verification of programs manipulating doubly-linked lists.

Cubicle is a new model checker for verifying safety properties of parameterized systems. It implements a parallel symbolic backward reachability procedure using Satisfiabilty Modulo Theories. Experiments done on classic and challenging mutual exclusion algorithms and cache coherence protocols show that Cubicle is effective and competitive with state-of-the-art model checkers.

This paper describes a novel decision procedure for quantifier-free linear integer arithmetic. Standard techniques usually relax the initial problem to the rational domain and then proceed either by projection (e.g. Omega-Test) or by branching/cutting methods (branch-and-bound, branch-and-cut, Gomory cuts). Our approach tries to bridge the gap between the two techniques: it interleaves an exhaustive search for a model with bounds inference. These bounds are computed provided an oracle capable of finding constant positive linear combinations of affine forms. We also show how to design an efficient oracle based on the Simplex procedure. Our algorithm is proved sound, complete, and terminating and is implemented in the Alt-Ergo theorem prover. Experimental results are promising and show that our approach is competitive with state-of-the-art SMT solvers.

SMT solvers can decide the satisfiability of ground formulas modulo a combination of built-in theories. Adding a built-in theory to a given SMT solver is a complex and time consuming task that requires internal knowledge of the solver. However, many theories can be easily expressed using first-order formulas. Unfortunately, since universal quantifiers are not handled in a complete way by SMT solvers, these axiomatics cannot be used as decision procedures. In this paper, we show how to extend a generic SMT solver to accept a custom theory description and behave as a decision procedure for that theory, provided that the described theory is complete and terminating in a precise sense. The description language consists of first-order axioms with triggers, an instantiation mechanism that is found in many SMT solvers. This mechanism, which usually lacks a clear semantics in existing languages and tools, is rigorously defined here; this definition can be used to prove completeness and termination of the theory. We demonstrate on two examples, how such proofs can be achieved in our formalism.

Keywords: Quantifiers, Triggers, SMT Solvers, Theories

We present a generic congruence closure algorithm for deciding ground formulas in the combination of the theory of equality with uninterpreted symbols and an arbitrary built-in solvable theory X. Our algorithm CC(X) is reminiscent of Shostak combination: it maintains a union-find data-structure modulo X from which maximal information about implied equalities can be directly used for congruence closure. CC(X) diverges from Shostak's approach by the use of semantical values for class representatives instead of canonized terms. Using semantical values truly reflects the actual implementation of the decision procedure for X. It also enforces to entirely rebuild the algorithm since global canonization, which is at the heart of Shostak combination, is no longer feasible with semantical values. CC(X) has been implemented in Ocaml and is at the core of Ergo, a new automated theorem prover dedicated to program verification.

Le problème SAT, qui consiste `a déterminer si une formule booléenne est satisfaisable, est un des problèmes NP-complets les plus célèbres et aussi un des plus étudiés. Basés initialement sur la procédure DPLL, les SAT-solvers modernes ont connu des progrès spectaculaires ces dix dernières années dans leurs performances, essentiellement grâce à deux optimisations: le retour en arrière non-chronologique et l'apprentissage par analyse des clauses conflits. Nous proposons dans cet article une étude formelle du fonctionnement de ces techniques ainsi qu'une réalisation en Ocaml d'un SAT-solver, baptisé SAT-MICRO, intégrant ces optimisations. Le fonctionnement de SAT-MICRO est décrit par un ensemble de règles d'inférence et la taille de son code, 70 lignes au total, permet d'envisager sa certification complète.

The problem of disjoint sets, also known as union-find, consists in maintaining a partition of a finite set within a data structure. This structure provides two operations: a function find returning the class of an element and a function union merging two classes. An optimal and imperative solution is known since 1975. However, the imperative nature of this data structure may be a drawback when it is used in a backtracking algorithm. This paper details the implementation of a persistent union-find data structure as efficient as its imperative counterpart. To achieve this result, our solution makes heavy use of imperative features and thus it is a significant example of a data structure whose side effects are safely hidden behind a persistent interface. To strengthen this last claim, we also detail a formalization using the Coq proof assistant which shows both the correctness of our solution and its observational persistence.

This paper details the design and implementation of Ocamlgraph, a highly generic graph library for the programming language Ocaml. This library features a large set of graph data structures---directed or undirected, with or without labels on vertices and edges, as persistent or mutable data structures, etc.---and a large set of graph algorithms. Algorithms are written independently from graph data structures, which allows combining user data structure (resp. algorithm) with Ocamlgraph algorithm (resp. data structure). Genericity is obtained through massive use of the Ocaml module system and its functions, the so-called functors.

Ergo is a little engine of proof dedicated to program verification. It fully supports quantifiers and directly handles polymorphic sorts. Its core component is CC(X), a new combination scheme for the theory of uninterpreted symbols parameterized by a built-in theory X. In order to make a sound integration in a proof assistant possible, Ergo is capable of generating proof traces for CC(X). Alternatively, Ergo can also be called interactively as a simple oracle without further verification. It is currently used to prove correctness of C and Java programs as part of the Why platform.

Le problème des classes disjointes, connu sous le nom de union-find, consiste à maintenir dans une structure de données une partition d'un ensemble fini. Cette structure fournit deux opérations : une fonction find déterminant la classe d'un élément et une fonction union réunissant deux classes. Une solution optimale et impérative, due à Tarjan, est connue depuis longtemps.

Cependant, le caractère impératif de cette structure de données devient gênant lorsqu'elle est utilisée dans un contexte où s'effectuent des retours en arrière (backtracking). Nous présentons dans cet article une version persistante de union-find dont la complexité est comparable à celle de la solution impérative. Pour obtenir cette efficacité, notre solution utilise massivement des traits impératifs. C'est pourquoi nous présentons également une preuve formelle de correction, pour s'assurer notamment du caractère persistant de cette solution.