The Constructive method for query containment checking (extended version)

We present a new method that checks Query Containment for queries with negated derived atoms and/or integrity constraints. Existing methods for Query Containment checking that deal with these cases do not check actually containment but another related property called uniform containment, which is a sufficient but not necessary condition for containment. Our method can be seen as an extension of the canonical databases approach beyond the class of conjunctive queries.Postprint (published version

A PC Chase

PC stands for path-conjunctive, the name of a class of queries and dependencies that we define over complex values with dictionaries. This class includes the relational conjunctive queries and embedded dependencies, as well as many interesting examples of complex value and oodb queries and integrity constraints. We show that some important classical results on containment, dependency implication, and chasing extend and generalize to this class

Context-Free Path Queries on RDF Graphs

Navigational graph queries are an important class of queries that canextract implicit binary relations over the nodes of input graphs. Most of the navigational query languages used in the RDF community, e.g. property paths in W3C SPARQL 1.1 and nested regular expressions in nSPARQL, are based on the regular expressions. It is known that regular expressions have limited expressivity; for instance, some natural queries, like same generation-queries, are not expressible with regular expressions. To overcome this limitation, in this paper, we present cfSPARQL, an extension of SPARQL query language equipped with context-free grammars. The cfSPARQL language is strictly more expressive than property paths and nested expressions. The additional expressivity can be used for modelling graph similarities, graph summarization and ontology alignment. Despite the increasing expressivity, we show that cfSPARQL still enjoys a low computational complexity and can be evaluated efficiently.Comment: 25 page

Query containment checking as a view updating problem

In this paper we present a new approach that handles query containment problems by expressing them as a view updating problem. Since this approach is independent of any particular view updating method, it provides a general framework that joins research efforts in both the query containment checking and view updating fields. In particular, the larger development of current view updating technology allows us to check properly query containment when considering negative-derived literals or integrity constraints. Existing methods for query containment checking that deal with these cases do not check actually containment but another related property called uniform containment, which is a sufficient but not necessary condition for containment. Therefore, an important outcome of our proposal is that, to the best of our knowledge, it is the first approach that checks true query containment instead of uniform query containment in the presence of negation and integrity constraints.Postprint (published version

Query Containment Using a DLR ABox

Query containment under constraints is the problem of determining whether the result of one query is contained in the result of another query for every database satisfying a given set of constraints. This problem is of particular importance in information integration and warehousing where, in addition to the constraints derived from the source schemas and the global schema, inter-schema constraints can be used to specify relationships between objects in different schemas. A theoretical framework for tackling this problem using the DLR logic has been established, and in this paper we show how the framework can be extended to a practical decision procedure. The proposed technique is to extend DLR with an Abox (a set of assertions about named individuals and tuples), and to transform query subsumption problems into DLR Abox satisfiability problems. We then show how such problems can be decided, via a reification transformation, using a highly optimised reasoner for the SHIQ description logic

Approximate Assertional Reasoning Over Expressive Ontologies

In this thesis, approximate reasoning methods for scalable assertional reasoning are provided whose computational properties can be established in a well-understood way, namely in terms of soundness and completeness, and whose quality can be analyzed in terms of statistical measurements, namely recall and precision. The basic idea of these approximate reasoning methods is to speed up reasoning by trading off the quality of reasoning results against increased speed

Erklären von Erfüllbarkeitsanfragen für Softwareproduktlinien

Many analyses have been proposed to ensure the correctness of the various models used throughout software product line development. However, these analyses often merely serve to detect such circumstances without providing any means for dealing with them once encountered. To aid the software product line developer in understanding the cause of defects, a new algorithm capable of explaining satisfiability queries in a software product line context is presented in this thesis. This algorithm finds explanations by using SAT solvers to extract minimal unsatisfiable subsets from the propositional formulas that express the defects. The algorithm is applied to feature model defects such as dead features and redundant constraints, automatic truth value propagations in configurations, and preprocessor annotations that are superfluous or cause dead code blocks. Using feature models and configurations from real software product lines of varying sizes, this approach is evaluated against an existing explanation approach based on Boolean constraint propagation. The results show that Boolean constraint propagation occasionally fails to find any explanation at all but is magnitudes faster than using minimal unsatisfiable subset extractors. In response, both algorithms are combined into a single one that is as fast as Boolean constraint propagation for the cases where that finds an explanation, but also finds an explanation for all the other cases.Viele Analysen wurden vorgeschlagen, um die Korrektheit der verschiedenen in der Entwicklung von Softwareproduktlinien genutzten Modelle zu gewährleisten. Allerdings dienen diese Analysen häufig lediglich dem Erkennen solcher Umstände, ohne Mittel zu liefern, sie zu lösen, sobald sie angetroffen wurden. Um dem Entwickler der Softwareproduktlinie das Verstehen der Ursache der Defekte zu erleichtern, wird in dieser Arbeit ein neuer Algorithmus zum Erklären von Erfüllbarkeitsanfragen im Kontext von Softwareproduktlinien vorgestellt. Dieser Algorithmus findet Erklärungen, indem mittels SAT-Solvern eine minimale unerfüllbare Teilmenge aus der aussagenlogischen Formel, die den Defekt ausdrückt, extrahiert wird. Der Algorithmus wird angewandt auf Defekte in Feature-Modellen wie tote Features und redundante Constraints, automatische Resolution von Wahrheitswerten in Konfigurationen sowie Präprozessorannotationen, die überflüssig sind oder tote Code-Blocks verursachen. Dieser Ansatz wird anhand von Feature-Modellen und Konfigurationen aus echten Softwareproduktlinien verschiedener Größen gegen einen existierenden, auf Boolean-Constraint-Propagation basierenden Ansatz zum Erklären evaluiert. Die Ergebnisse zeigen, dass Boolean-Constraint-Propagation gelegentlich gar keine Erklärung findet, aber um Größenordnungen schneller als mittels Extraktoren für minimale unerfüllbare Teilmengen ist. Daraufhin werden beide Algorithmen in einem einzigen verbunden, der so schnell wie Boolean-Constraint-Propagation ist, wenn dieser eine Erklärung findet, aber auch eine Erklärung in allen übrigen Fällen findet