Combining Theories with Shared Set Operations

Etessami et al. [5] showed that satisfiability of two-variable first order logic \(\mathrm {FO}^2\)[<] on word models is Nexptime-complete. We extend this upper bound to the slightly stronger logic \(\mathrm {FO}^2\)[\(<,succ ,\equiv \)], which allows checking whether a word position is congruent to r modulo q, for some divisor q and remainder r. If we allow the more powerful modulo counting quantifiers of Straubing, Therien et al. [22] (we call this two-variable fragment FOmod \(^2\)[\(<,succ \)]), satisfiability becomes Expspace-complete. A more general counting quantifier, FOunC\(^2\)[\(<,succ \)], makes the logic undecidable.

Weighted First-Order Model Counting (WFOMC) computes the weighted sum of the models of a first-order logic theory on a given finite domain. First-Order Logic theories that admit polynomial-time WFOMC w.r.t domain cardinality are called domain liftable. We introduce the concept of lifted interpretations as a tool for formulating closed forms for WFOMC. Using lifted interpretations, we reconstruct the closed-form formula for polynomial-time FOMC in the universally quantified fragment of FO2, earlier proposed by Beame et al. We then expand this closed-form to incorporate cardinality constraints, existential quantifiers, and counting quantifiers (a.k.a C2) without losing domain-liftability. Finally, we show that the obtained closed-form motivates a natural definition of a family of weight functions strictly larger than symmetric weight functions.

Enriching logic formalisms with counting capabilities is an important task in view of the needs of many application areas, ranging from database theory to formal verification. In this paper, we consider a very expressive language obtained by enriching linear integer arithmetic with free function symbols and cardinality constraints for interpreted sets. We obtain positive results for a flat fragment via a reduction to decidability of Presburger arithmetic with unary counting quantifiers (Schweikhart in Arithmetic, first-order logic, and counting quantifiers, ACM TOCL, New York, 2004). We isolate also an easier simple flat subfragment, whose satisfiability is in NP, and we show that this subfragment is adequate to formalize problems arising in the area of the verification of fault-tolerant distributed algorithms. We finally discuss our first implementation, the related experimental results, as well as further algorithmic problems suggested by model-checking applications.

We extend the weak monadic second-order logic of one successor on finite strings (M2L-STR) to symbolic alphabets by allowing character predicates to range over decidable quantifier free theories instead of finite alphabets. We call this logic, which is able to describe sequences over complex and potentially infinite domains, symbolic M2L-STR (S-M2L-STR). We then present a decision procedure for S-M2L-STR based on a reduction to symbolic finite automata, a decidable extension of finite automata that allows transitions to carry predicates and can therefore model symbolic alphabets. The reduction constructs a symbolic automaton over an alphabet consisting of pairs of symbols where the first element of the pair is a symbol in the original formula's alphabet, while the second element is a bit-vector. To handle this modified alphabet we show that the Cartesian product of two decidable Boolean algebras (e.g., the formula's one and the bit-vector's one) also forms a decidable Boolean algebras. To make the decision procedure practical, we propose two efficient representations of the Cartesian product of two Boolean algebras, one based on algebraic decision diagrams and one on a variant of Shannon expansions. Finally, we implement our decision procedure and evaluate it on more than 10,000 formulas. Despite the generality, our implementation has comparable performance with the state-of-the-art M2L-STR solvers.

The non-exact projective NPNP (NP3) Boolean matching problem is practically significant in the applications of technology mapping, logic verification, and hardware security. However, its difficulty compels an unsatisfactory running time, and conventional algorithms for the basic NPNP Boolean matching problem perform terribly on the non-exact and projective type. In this paper, we propose a novel algorithm to solve this newly rising NP3 Boolean matching problem, and multiple types of optimization were applied to further improve the performance. Experimental results indicate that our algorithm has outstanding outcomes.

We extend the terminological formalism of the well-known description logic ALC from concept inclusions (CIs) to more general constraints formulated in the quantifier-free fragment of Boolean Algebra with Presburger Arithmetic (QFBAPA). In QFBAPA one can formulate Boolean combinations of inclusion constraints and numerical constraints on the cardinalities of sets.Our new formalism extends, on the one hand, so-called cardinality restrictions on concepts, which have been introduced two decades ago, and on the other hand the recently introduced statistical knowledge bases. Though considerably more expressive, our formalism has the same complexity (NExpTime) as cardinality restrictions on concepts. We will also introduce a restricted version of our formalism for which the complexity is ExpTime. This yields the until now unknown exact complexity of the consistency problem for statistical knowledge bases.

BSP trees have been shown to provide an effective representation of polyhedra through the use of spatial subdivision, and are an alternative to the topologically based b-reps. While bsp tree algorithms are known for a number of important operations, such as rendering, no previous work on bsp trees has provided the capability of performing boolean set operations between two objects represented by bsp trees, i.e. there has been no closed boolean algebra when using bsp trees. This paper presents the algorithms required to perform such operations. In doing so, a distinction is made between the semantics of polyhedra and the more fundamental mechanism of spatial partitioning. Given a partitioning of a space, a particular semantics is induced on the space by associating attributes required by the desired semantics with the cells of the partitioning. So, for example, polyhedra are obtained simply by associating a boolean attribute with each cell. Set operations on polyhedra are then constructed on top of the operation of merging spatial partitionings. We present then the algorithm for merging two bsp trees independent of any attributes/semantics, and then follow this by the additional algorithmic considerations needed to provide set operations on polyhedra. The result is a simple and numerically robust algorithm for set operations.

A systematic procedure is presented for generating Boolean logic equations that represent the desired control action to be carried out by a discrete logic controller. A key component of the controller design is the specification of set and reset operations that define the next value of each state variable in the Boolean logic equations for the controller. The logic equations can be implemented on a PLC or PC in order to realize the desired control action. Two examples are given to illustrate the procedure.

The subject matter of this paper belongs to the general theory of sets.The objectives here are the examinations of the structure of classes of sets which are closed under various finite and transfinite set operations and those transformations which preserve these operations.The major results of this paper are partial extensions of (a) the well known theory of cr-algebras (e.g.[4]), (b) the work of E. Marczewski [l] on isomorphisms, (c) the work of R. Sikorski [2] on tr-homomorphisms and (d) the work of A .Tarski [3 ] on fields of sets and set functions.Three classes of sets-the algebra, raz-algebra and total algebra-as well as four transformations-the w-homomorphism, weak isomorphism, raz-isomorphism, and total isomorphism-are studied.A class X of sets is an algebra if it is closed under finite set operations, i.e. addition of two sets and complementation.Analogically X is an w-algebra if X is closed under tw-operations, i.e. complementations and addition of not more than m sets, where m is an arbitrary fixed cardinal number.X is a total algebra if it is closed under all operations, i.e. complementation and arbitrary addition.Two classes of sets, X and £, are weakly isomorphic if X and £ considered as partially ordered by the relation of proper inclusion are similar.X and £ are zra-isomorphic if they have the same properties from the point of view of »«-operations; and, finally, X and £ are

In this paper we extend a decision procedure for the Boolean algebra of finite sets with cardinality constraints (ℒ |⋅| ) to a decision procedure for ℒ |⋅| extended with set terms denoting finite integer intervals (ℒ [] ). In ℒ [] interval limits can be integer linear terms including 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 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 } (‘setlog’) 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.

SAT solving has gained tremendous interest. On the practical side there have been considerable performance improvements, due to new highly efficient algorithms, new heuristics, and optimized data structures. There are new applications and reformulations of important classical problems, mainly in the context of formal methods, where SAT solving is also applied successfully in an industrial setting. These applications range from equivalence checking, configuration, over model checking to test case generation. SAT is becoming one of the most important core technology in all these areas. Many applications actually use Satisfiability Modulo Theory (SMT), which can be seen as an extension of SAT solving. SMT has it roots in automated theorem proving. But it heavily relies on SAT technology. We discuss some key technologies in practical SAT solving, e.g. how to write a fast solver, some aspects in lifting propositional SAT technology to richer domains, how competitions can help to improve the state-of-the-art and finally touch on applications in model checking, hardware and software verification.

Worst case examples for operations on OBDDs

Optimized solvers for the Boolean satisfiability (SAT) problem have many applications in areas such as hardware and software verification, FPGA routing, planning, and so forth. Further uses are complicated by the need to express "counting constraints" in conjunctive normal form (CNF). Expressing such constraints by pure CNF leads to more complex SAT instances. Alternatively, those constraints can be handled by integer linear programming (ILP), but generic ILP solvers may ignore the Boolean nature of 0-1 variables. Therefore, specialized 0-1 ILP solvers extend SAT solvers to handle these so-called "pseudo-Boolean" (PB) constraints. This work provides an update on the on-going competition between generic ILP techniques and specialized 0-1 ILP techniques. To make a fair comparison, we generalize recent ideas for fast SAT-solving to more general 0-1 ILP problems that may include counting constraints and optimization. This generalization is embodied in our PB constraint solver and optimizer PBS, which is compared with state-of-the-art CNF and generic ILP solvers. Another aspect of our comparison is the evaluation on 0-1 ILP benchmarks that originate in electronic design automation (EDA) but that cannot be directly solved by an SAT solver. Specifically, we solve instances of the max-SAT and max-ONEs optimization problems, which seek to maximize the number of satisfied clauses and the "true" values over all satisfying assignments, respectively. Those problems have straightforward applications to SAT-based routing and are additionally important due to reductions from max-cut, max-clique, and min vertex cover. Our experimental results show that specialized 0-1 techniques implemented in PBS tend to outperform generic ILP techniques on Boolean optimization problems, as well as on general EDA SAT problems.

Separation logic (SL) is a widely used formalism for verifying programs that manipulate dynamically allocated memory, relying on the separating conjunction $$\star $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mo>⋆</mml:mo> </mml:math> to combine disjoint heap structures. The standard approach in SL lacks the expressive power to handle overlaid data structures where multiple structures share some locations. We consider a logic that extends SL with a new separating conjunction operator "Image missing", enabling the composition of heaps with shared locations that allocate distinct fields. Our fragment supports generic inductive definitions and introduces set variables to constrain the locations shared by overlapping structures. We prove that the satisfiability problem for this fragment is in Nexptime , by reducing it to the satisfiability problem in BAPA [11], a decidable logic combining Boolean algebra of sets and Presburger arithmetic.

In this paper we study the logical aspects of branching automata, as defined by Lodaya and Weil. We first prove that the class of languages of finite N-free posets recognized by branching automata is closed under complementation. Then we define a logic, named P-MSO as it is a extension of monadic second-order logic with Presburger arithmetic, and show that it is precisely as expressive as branching automata. As a consequence of the effectiveness of the construction of one formalism from the other, the P-MSO theory of the class of all finite N-free posets is decidable.