5 research outputs found

    Analyzing Satisfiability and Refutability in Selected Constraint Systems

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    This dissertation is concerned with the satisfiability and refutability problems for several constraint systems. We examine both Boolean constraint systems, in which each variable is limited to the values true and false, and polyhedral constraint systems, in which each variable is limited to the set of real numbers R in the case of linear polyhedral systems or the set of integers Z in the case of integer polyhedral systems. An important aspect of our research is that we focus on providing certificates. That is, we provide satisfying assignments or easily checkable proofs of infeasibility depending on whether the instance is feasible or not. Providing easily checkable certificates has become a much sought after feature in algorithms, especially in light of spectacular failures in the implementations of some well-known algorithms. There exist a number of problems in the constraint-solving domain for which efficient algorithms have been proposed, but which lack a certifying counterpart. When examining Boolean constraint systems, we specifically look at systems of 2-CNF clauses and systems of Horn clauses. When examining polyhedral constraint systems, we specifically look at systems of difference constraints, systems of UTVPI constraints, and systems of Horn constraints. For each examined system, we determine several properties of general refutations and determine the complexity of finding restricted refutations. These restricted forms of refutation include read-once refutations, in which each constraint can be used at most once; literal-once refutations, in which for each literal at most one constraint containing that literal can be used; and unit refutations, in which each step of the refutation must use a constraint containing exactly one literal. The advantage of read-once refutations is that they are guaranteed to be short. Thus, while not every constraint system has a read-once refutation, the small size of the refutation guarantees easy checkability

    Efficient Generation of Craig Interpolants in Satisfiability Modulo Theories

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    The problem of computing Craig Interpolants has recently received a lot of interest. In this paper, we address the problem of efficient generation of interpolants for some important fragments of first order logic, which are amenable for effective decision procedures, called Satisfiability Modulo Theory solvers. We make the following contributions. First, we provide interpolation procedures for several basic theories of interest: the theories of linear arithmetic over the rationals, difference logic over rationals and integers, and UTVPI over rationals and integers. Second, we define a novel approach to interpolate combinations of theories, that applies to the Delayed Theory Combination approach. Efficiency is ensured by the fact that the proposed interpolation algorithms extend state of the art algorithms for Satisfiability Modulo Theories. Our experimental evaluation shows that the MathSAT SMT solver can produce interpolants with minor overhead in search, and much more efficiently than other competitor solvers.Comment: submitted to ACM Transactions on Computational Logic (TOCL

    Incrementally Closing Octagons

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    The octagon abstract domain is a widely used numeric abstract domain expressing relational information between variables whilst being both computationally efficient and simple to implement. Each element of the domain is a system of constraints where each constraint takes the restricted form ±xi±xj≤c. A key family of operations for the octagon domain are closure algorithms, which check satisfiability and provide a normal form for octagonal constraint systems. We present new quadratic incremental algorithms for closure, strong closure and integer closure and proofs of their correctness. We highlight the benefits and measure the performance of these new algorithms

    Efficient querying and learning in probabilistic and temporal databases

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    Probabilistic databases store, query, and manage large amounts of uncertain information. This thesis advances the state-of-the-art in probabilistic databases in three different ways: 1. We present a closed and complete data model for temporal probabilistic databases and analyze its complexity. Queries are posed via temporal deduction rules which induce lineage formulas capturing both time and uncertainty. 2. We devise a methodology for computing the top-k most probable query answers. It is based on first-order lineage formulas representing sets of answer candidates. Theoretically derived probability bounds on these formulas enable pruning low-probability answers. 3. We introduce the problem of learning tuple probabilities which allows updating and cleaning of probabilistic databases. We study its complexity, characterize its solutions, cast it into an optimization problem, and devise an approximation algorithm based on stochastic gradient descent. All of the above contributions support consistency constraints and are evaluated experimentally.Probabilistische Datenbanken können große Mengen an ungewissen Informationen speichern, anfragen und verwalten. Diese Doktorarbeit treibt den Stand der Technik in diesem Gebiet auf drei Arten vorran: 1. Ein abgeschlossenes und vollständiges Datenmodell für temporale, probabilistische Datenbanken wird präsentiert. Anfragen werden mittels Deduktionsregeln gestellt, welche logische Formeln induzieren, die sowohl Zeit als auch Ungewissheit erfassen. 2. Ein Methode zur Berechnung der k Anworten höchster Wahrscheinlichkeit wird entwickelt. Sie basiert auf logischen Formeln erster Stufe, die Mengen an Antwortkandidaten repräsentieren. Beschränkungen der Wahrscheinlichkeit dieser Formeln ermöglichen das Kürzen von Antworten mit niedriger Wahrscheinlichkeit. 3. Das Problem des Lernens von Tupelwahrscheinlichkeiten für das Aktualisieren und Bereiningen von probabilistischen Datenbanken wird eingeführt, auf Komplexität und Lösungen untersucht, als Optimierungsproblem dargestellt und von einem stochastischem Gradientenverfahren approximiert. All diese Beiträge unterstützen Konsistenzbedingungen und wurden experimentell analysiert
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