Building small equality graphs for deciding equality logic with uninterpreted functions

The logic of Equalities with Uninterpreted Functions is used in the formal verification community mainly for proofs of equivalence: proving that two versions of a hardware design are the same, or that input and output of a compiler are semantically equivalent are two prominent examples of such proofs. We introduce a new decision procedure for this logic that generalizes two leading decision procedures that were published in the last few years: the Positive Equality approach suggested by Bryant et al. [Exploiting positive equality in a logic of equality with uninterpreted functions, in: Proc. 11th Intl. Conference on Computer Aided Verification (CAV’99), 1999], and the Range-Allocation algorithm suggested by Pnueli et al. [The small model property: how small can it be? Information and Computation 178 (1) (2002) 279–293]. Both of these methods reduce this logic to pure Equality Logic (without Uninterpreted Functions), and then, due to the small model property that such formulas have, find a small domain to each variable that is sufficiently large to maintain the satisfiability of the formula. The state-space spanned by these domains is then traversed with a BDD-based engine. The Positive Equality approach identifies terms that have a certain characteristic in the original formula (before the reduction to pure Equality Logic) and replaces them with unique constants. The Range-Allocation algorithm analyzes the structure of the formula after the reduction to equality logic with a graph-based procedure to allocate a small set of values to each variable. The former, therefore, has an advantage when a large subset of the terms can be replaced with constants, and disadvantage in the other cases. In this paper we essentially merge the two methods, while improving both with a more careful analysis of the formula’s structure. We show that the new method is provably dominant over both methods, theoretically as well as empirically.¹     

A new universal approximation result for fuzzy systems,which reflects CNF DNF duality

There are two main fuzzy system methodologies for translating expert rules into a logical formula: In Mamdani's methodology, we get a DNF formula (disjunction of conjunctions), and in a methodology which uses logical implications, we get, in effect, a CNF formula (conjunction of disjunctions). For both methodologies, universal approximation results have been proven which produce, for each approximated function f(x), two different approximating relations R_DNF(x, y) and R_CNF(x, y). Since, in fuzzy logic, there is a known relation F_CNF(x) ≤ F_DNF(x) between CNF and DNF forms of a propositional formula F, it is reasonable to expect that we would be able to prove the existence of approximations for which a similar relation R_CNF(x, y) ≤ R_DNF(x, y) holds. Such existence is proved in our paper. © 2002 Wiley Periodicals, Inc.     

Quantitative Separation Logic and Programs with Lists

This paper presents an extension of a decidable fragment of Separation Logic for singly-linked lists, defined by Berdine et al. (2004). Our main extension consists in introducing atomic formulae of the form ls ^k (x, y) describing a list segment of length k, stretching from x to y, where k is a logical variable interpreted over positive natural numbers, that may occur further inside Presburger constraints. We study the decidability of the full first-order logic combining unrestricted quantification of arithmetic and location variables. Although the full logic is found to be undecidable, validity of entailments between formulae with the quantifier prefix in the language $^* {$_\mathbbN, "_\mathbbN}^*\exists^* \{\exists_{\bf \mathbb{N}}, \forall_{\bf \mathbb{N}}\}^* is decidable. We provide here a model theoretic method, based on a parametric notion of shape graphs. We have implemented our decision technique, providing a fully automated framework for the verification of quantitative properties expressed as pre- and post-conditions on programs working on lists and integer counters.     

Filter theory of BL algebras

In this paper we consider fundamental properties of some types of filters (Boolean, positive implicative, implicative and fantastic filters) of BL algebras defined in Haveshki et al. (Soft Comput 10:657–664, 2006) and Turunen (Arch Math Logic 40:467–473, 2001). It is proved in Haveshki et al. (2006) that if F is a maximal and (positive) implicative filter then it is a Boolean filter. In that paper there is an open problem Under what condition are Boolean filters positive implicative filters? One of our results gives an answer to the problem, that is, we need no more conditions. Moreover, we give simple characterizations of those filters by an identity form ? x, y(t(x, y) ∈ F), where t(x, y) is a term containing x, y.      

On a family of copulas constructed from the diagonal section

We characterize the class of copulas that can be constructed from the diagonal section by means of the functional equation C(x,y)+|x−y|=C(x∨y,x∨y), for all (x,y) in the unit square such that C(x,y)>0. Some statistical properties of this class are given.     

Approximate Solutions of Polynomial Equations

In this paper, we introduce “approximate solutions" to solve the following problem: given a polynomial F(x, y) over Q, where x represents an n -tuple of variables, can we find all the polynomials G(x) such that F(x, G(x)) is identically equal to a constant c in Q ? We have the following: let F(x, y) be a polynomial over Q and the degree of y in F(x, y) be n. Either there is a unique polynomial g(x)  ∈ Q [ x ], with its constant term equal to 0, such that F(x, y)  = ∑_j = 0ⁿc_j(y − g(x))^jfor some rational numbers c_j, hence, F(x, g(x)  + a)  ∈ Q for all a ∈ Q, or there are at most t distinct polynomials g₁(x),⋯ , g_t(x), t ≤ n, such that F(x, g_i(x))  ∈ Q for 1  ≤ i ≤ t. Suppose that F(x, y) is a polynomial of two variables. The polynomial g(x) for the first case, or g₁(x),⋯ , g_t(x) for the second case, are approximate solutions of F(x, y), respectively. There is also a polynomial time algorithm to find all of these approximate solutions. We then use Kronecker’s substitution to solve the case of F(x, y).     

Inapproximability of the Tutte polynomial

The Tutte polynomial of a graph G is a two-variable polynomial T(G;x,y) that encodes many interesting properties of the graph. We study the complexity of the following problem, for rationals x and y: take as input a graph G, and output a value which is a good approximation to T(G;x,y). Jaeger et al. have completely mapped the complexity of exactly computing the Tutte polynomial. They have shown that this is #P-hard, except along the hyperbola (x-1)(y-1)=1 and at four special points. We are interested in determining for which points (x,y) there is a fully polynomial randomised approximation scheme (FPRAS) for T(G;x,y). Under the assumption RP≠NP, we prove that there is no FPRAS at (x,y) if (x,y) is in one of the half-planes x<-1 or y<-1 (excluding the easy-to-compute cases mentioned above). Two exceptions to this result are the half-line x<-1,y=1 (which is still open) and the portion of the hyperbola (x-1)(y-1)=2 corresponding to y<-1 which we show to be equivalent in difficulty to approximately counting perfect matchings. We give further intractability results for (x,y) in the vicinity of the origin. A corollary of our results is that, under the assumption RP≠NP, there is no FPRAS at the point (x,y)=(0,1-λ) when λ>2 is a positive integer. Thus, there is no FPRAS for counting nowhere-zero λ flows for λ>2. This is an interesting consequence of our work since the corresponding decision problem is in P for example for λ=6. Although our main concern is to distinguish regions of the Tutte plane that admit an FPRAS from those that do not, we also note that the latter regions exhibit different levels of intractability. At certain points (x,y), for example the integer points on the x-axis, or any point in the positive quadrant, there is a randomised approximation scheme for T(G;x,y) that runs in polynomial time using an oracle for an NP predicate. On the other hand, we identify a region of points (x,y) at which even approximating T(G;x,y) is as hard as #P.     

A predictor-corrector form of the numerov method for coupled equations

A new algorithm is presented for solving nonlinear second-order coupled differential equations of the form y′ = F(x,y). Modifications of the standard Numerov procedure have resulted in a rapid, noniterative, predictor-corrector form without matrix inversion and with improved accuracy. Comparisons with the usual Numerov and de Vogelaere methods are presented for the homogeneous case F(x,y) = -G(x)y often encountered in quantum scattering theory. Tests are also presented of a version with variable step size and with stabilization by orthogonalization of the solutions at internally determined. intervals.     

The SAT-based Approach to Separation Logic

The SAT-based approach to the decision problem for expressive, decidable, quantifier-free first-order theories has been investigated with remarkable results at least since 1993. One such theory, successfully employed in the formal verification of complex, infinite state systems, is Separation Logic (SL), which combines Boolean logic with arithmetic constraints of the form x − y ⋈ c, where ⋈ is ≤, <, >, ≥, =, or ≠. The SAT-based approach to SL was first proposed and implemented in 1999: the results in terms of performance were good, and since then a number of other systems for SL have appeared. In this paper we focus on the problem of building efficient SAT-based decision procedures for SL. We present the basic procedure and four optimizations that improve dramatically its effectiveness in most cases: (a) IS ₂ preprocessing, (b) early pruning, (c) model reduction, and (d) best reason detection. For each technique we give an example of how it might improve the performance. Furthermore, for the first three techniques, we give a pseudo-code representation and formally state the soundness and completeness of the resulting optimized procedure. We also show how it is possible to check the satisfiability of valuations involving constraints of the form x − y < c using the Bellman–Ford algorithm. Lastly, we present an extensive comparative experimental analysis, showing that our solver TSAT++, built along the lines described in this paper, is currently the state of the art on various classes of problems, including randomly generated, hand-made, and real-world instances.     

Vanquishing the XCB Question: The Methodological Discovery of the Last Shortest Single Axiom for the Equivalential Calculus

With the inclusion of an effective methodology, this article answers in detail a question that, for a quarter of a century, remained open despite intense study by various researchers. Is the formula XCB=e(x,e(e(e(x,y),e(z,y)),z)) a single axiom for the classical equivalential calculus when the rules of inference consist of detachment (modus ponens) and substitution Where the function e represents equivalence, this calculus can be axiomatized quite naturally with the formulas e(x,x), e(e(x,y),e(y,x)), and e(e(x,y),e(e(y,z),e(x,z))), which correspond to reflexivity, symmetry, and transitivity, respectively. (We note that e(x,x) is dependent on the other two axioms.) Heretofore, thirteen shortest single axioms for classical equivalence of length eleven had been discovered, and XCB was the only remaining formula of that length whose status was undetermined. To show that XCB is indeed such a single axiom, we focus on the rule of condensed detachment, a rule that captures detachment together with an appropriately general, but restricted, form of substitution. The proof we present in this paper consists of twenty-five applications of condensed detachment, completing with the deduction of transitivity followed by a deduction of symmetry. We also discuss some factors that may explain in part why XCB resisted relinquishing its treasure for so long. Our approach relied on diverse strategies applied by the automated reasoning program OTTER. Thus ends the search for shortest single axioms for the equivalential calculus.     

Generalized Gaussian quadrature rules over regions with parabolic edges

This paper presents a generalized Gaussian quadrature method for numerical integration over regions with parabolic edges. Any region represented by R ₁={(x, y)| a≤x≤b, f(x)≤y≤g(x)} or R ₂={(x, y)| a≤y≤b, f(y)≤x≤g(y)}, where f(x), g(x), f(y) and g(y) are quadratic functions, is a region bounded by two parabolic arcs or a triangular or a rectangular region with two parabolic edges. Using transformation of variables, a general formula for integration over the above-mentioned regions is provided. A numerical method is also illustrated to show how to apply this formula for other regions with more number of linear and parabolic sides. The method can be used to integrate a wide class of functions including smooth functions and functions with end-point singularities, over any two-dimensional region, bounded by linear and parabolic edges. Finally, the computational efficiency of the derived formulae is demonstrated through several numerical examples.     

Checking If There Exists a Monotonic Function That Is Consistent with the Measurements: An Efficient Algorithm

In many problems in science and engineering ranging from astrophysics to geosciences to financial analysis, we know that a physical quantity y depends on the physical quantity x, i.e., y = f(x) for some function f(x), and we want to check whether this dependence is monotonic. Specifically, finitely many measurements of x_i and y = f(x) have been made, and we want to check whether the results of these measurements are consistent with the monotonicity of f(x). An efficient parallelizable algorithm is known for solving this problem when the values x_i are known precisely, while the values y_i are known with interval uncertainty. In this paper, we extend this algorithm to a more general (and more realistic) situation when both x_i and y_i are known with interval uncertainty.     

A sufficient condition for pancyclic graphs

In 2005, Rahman and Kaykobad proved that if G is a connected graph of order n such that d(x)+d(y)+d(x,y)n+1 for each pair x, y of distinct nonadjacent vertices in G, where d(x,y) is the length of a shortest path between x and y in G, then G has a Hamiltonian path [Inform. Process. Lett. 94 (2005) 37–41]. In 2006 Li proved that if G is a 2-connected graph of order n3 such that d(x)+d(y)+d(x,y)n+2 for each pair x,y of nonadjacent vertices in G, then G is pancyclic or G=K_n/2,n/2 where n4 is an even integer [Inform. Process. Lett. 98 (2006) 159–161]. In this work we prove that if G is a 2-connected graph of order n such that d(x)+d(y)+d(x,y)n+1 for all pairs x, y of distinct nonadjacent vertices in G, then G is pancyclic or G belongs to one of four specified families of graphs.     

Value monoids of zero-dimensional valuations of rank 1

Classically, Gröbner bases are computed by first prescribing a fixed monomial order. Moss Sweedler suggested an alternative in the mid-1980s and developed a framework for performing such computations by using valuation rings in place of monomial orders. We build on these ideas by providing a class of valuations on K(x,y) that are suitable for this framework. We then perform such computations for ideals in the polynomial ring K[x,y]. Interestingly, for these valuations, some ideals have finite Gröbner bases with respect to a valuation that are not Gröbner bases with respect to any monomial order, whereas other ideals only have Gröbner bases that are infinite.     

Functional expansions for nonlinear discrete-time systems

Given an input-output map associated with a nonlinear discrete-time state equationx(t + 1) =f(x(t);u(t)) and a nonlinear outputy(t) =h(x(t)), we present a method for obtaining a “discrete Volterra series” representation of the outputy(t) in terms of the controlsu(0), ...,u(t − 1). The proof is based on Taylor-type expansions of the iterated composition of analytic functions. It allows us to make an explicit construction of each kernel, that is, each coefficient of the series expansion ofy(t) in powers of the controls. This is achieved by making use of successive directional derivatives associated with a family of vector fields which are deduced from the discrete state equations. We discuss the use of these vector fields for the analysis and control of nonlinear discrete-time systems. This work was carried out while D. Normand-Cyrot was working at the I.A.S.I. (from March to October 1984) and with the financial support of the Italian C.N.R. (Consiglio Nazionale delle Ricerche).     

On estimation of the probability of absence of collisions of some random mappings

Let X and Y be finite sets and φ: (X,Y) →Y be a mapping. Consider a random mapping i → φ(x_i,y_i), where x_i are arbitrarily chosen from the set X, whereas (y_i) is a random sample from Y without replacement. A two-sided bound is derived for the probability of absence of collisions of this mapping. A case of mapping, defined as φ(x, y)=x+ y modulo n, is considered in particular. The results may be used in the selection of identification codes. Translated from Kibernetika i Sistemnyi Analiz, No. 1, pp. 132–137, January–February, 2000.     

The improved split-step backward Euler method for stochastic differential delay equations

A new, improved split-step backward Euler method is introduced and analysed for stochastic differential delay equations (SDDEs) with generic variable delay. The method is proved to be convergent in the mean-square sense under conditions (Assumption 3.1) that the diffusion coefficient g(x, y) is globally Lipschitz in both x and y, but the drift coefficient f(x, y) satisfies the one-sided Lipschitz condition in x and globally Lipschitz in y. Further, the exponential mean-square stability of the proposed method is investigated for SDDEs that have a negative one-sided Lipschitz constant. Our results show that the method has the unconditional stability property, in the sense, that it can well reproduce stability of the underlying system, without any restrictions on stepsize h. Numerical experiments and comparisons with existing methods for SDDEs illustrate the computational efficiency of our method.     

New explicit filters and smoothers for diffusions with nonlinear drift and measurements

The optimal least-squares filtering of a diffusion x(t) from its noisy measurements {y(τ); 0 τ t} is given by the conditional mean E[x(t)|y(τ); 0 τ t]. When x(t) satisfies the stochastic diffusion equation dx(t) = f(x(t)) dt + dw(t) and y(t) = ∫₀^tx(s) ds + b(t), where f(·) is a global solution of the Riccati equation /xf(x) + f(x)² = f(x)² = αx² + βx + γ, for some , and w(·), b(·) are independent Brownian motions, Benes gave an explicit formula for computing the conditional mean. This paper extends Benes results to measurements y(t) = ∫₀^tx(s) ds + ∫₀^t dx(s) + b(t) (and its multidimensional version) without imposing additional conditions on f(·). Analogous results are also derived for the optimal least-squares smoothed estimate E[x(s)|y(τ); 0 τ t], s < t. The methodology relies on Girsanov's measure transformations, gauge transformations, function space integrations, Lie algebras, and the Duncan-Mortensen-Zakai equation.     

The iterated defect correction methods for singular two-point boundary value problems

In this paper, the iterated defect correction (IDeC) techniques based on the centered Euler method for the equivalent first order system of the singular two-point boundary value problem in linear case (x ^α y′(x))′ = f(x), y(0) = a,y(1) = b, where 0 < α < 1 are considered. By using the asymptotic expansion of the global error, it is analyzed that the IDeC methods improved the approximate results by means of IDeC steps and the degree of the interpolating polynomials used. Some numerical examples from the literature are given in illustration of this theory.