From Causes for Database Queries to Repairs and Model-Based Diagnosis and Back

In this work we establish and investigate connections between causes for query answers in databases, database repairs wrt. denial constraints, and consistency-based diagnosis. The first two are relatively new research areas in databases, and the third one is an established subject in knowledge representation. We show how to obtain database repairs from causes, and the other way around. Causality problems are formulated as diagnosis problems, and the diagnoses provide causes and their responsibilities. The vast body of research on database repairs can be applied to the newer problems of computing actual causes for query answers and their responsibilities. These connections, which are interesting per se, allow us, after a transition -inspired by consistency-based diagnosis- to computational problems on hitting sets and vertex covers in hypergraphs, to obtain several new algorithmic and complexity results for database causality.Comment: To appear in Theory of Computing Systems. By invitation to special issue with extended papers from ICDT 2015 (paper arXiv:1412.4311

An introduction to Graph Data Management

A graph database is a database where the data structures for the schema and/or instances are modeled as a (labeled)(directed) graph or generalizations of it, and where querying is expressed by graph-oriented operations and type constructors. In this article we present the basic notions of graph databases, give an historical overview of its main development, and study the main current systems that implement them

Anticipation as prediction in the predication of data types

Every object in existence has its type. Every subject in language has its predicate. Every intension in logic has its extension. Each therefore has two levels but with the fundamental problem of the relationship between the two. The formalism of set theory cannot guarantee the two are co-extensive. That has to be imposed by the axiom of extensibility, which is inadequate for types as shown by Bertrand Russell's rami ed type theory, for language as by Henri Poincar e's impredication and for intension unless satisfying Port Royal's de nitive concept. An anticipatory system is usually de ned to contain its own future state. What is its type? What is its predicate? What is its extension? Set theory can well represent formally the weak anticipatory system, that is in a model of itself. However we have previously shown that the metaphysics of process category theory is needed to represent strong anticipation. Time belongs to extension not intension. The apparent prediction of strong anticipation is really in the structure of its predication. The typing of anticipation arises from a combination of and | respectively (co) multiplication of the (co)monad induced by adjointness of the system's own process. As a property of cartesian closed categories this predication has signi cance for all typing in general systems theory including even in the de nition of time itself

Sensitivity of the Physical Database Design to Changes in Underlying Factors

Several articles have reported on the optimization of the complete physical database design or significant parts of it. However, few results are available on the sensitivity of the physical database design to change in underlying factors that influence the design decisions. Such tenths would be of significant practical value in both the design of the initial physical database and its subsequent restructuring. This paper considers underlying factors related to logical data structure, queries, computer system and physical implementation. An experimental design based on these factors is developed and experiments are conducted to determine the sensitivity effects, and these are reported and discussed

A Survey of Hashing Techniques for High Performance Computing

Hashing is a well-known and widely used technique for providing O(1) access to large files on secondary storage and tables in memory. Hashing techniques were introduced in the early 60s. The term hash function historically is used to denote a function that compresses a string of arbitrary input to a string of fixed length. Hashing finds applications in other fields such as fuzzy matching, error checking, authentication, cryptography, and networking. Hashing techniques have found application to provide faster access in routing tables, with the increase in the size of the routing tables. More recently, hashing has found applications in transactional memory in hardware. Motivated by these newly emerged applications of hashing, in this paper we present a survey of hashing techniques starting from traditional hashing methods with greater emphasis on the recent developments. We provide a brief explanation on hardware hashing and a brief introduction to transactional memory