Computing candidate keys of relational operators for optimizing rewrite-based provenance computation : key property module

Data provenance provides information about the origin of data, and has long attracted the attention of the database community. It has been proven to be essential for a wide range of use cases from debugging of data and queries to probabilistic databases. There exist different techniques for computing the data provenance of a query. However, even sophisticated database optimizers are usually incapable of producing an efficient execution plan for provenance computations because of their inherent complexity and unusual structure. In this work, I develop the key property module, as part of the heuristic optimization techniques for rewrite-based provenance systems to address this problem and present an implementation of this module in the GProM provenance middle-ware system. The key property stores the set of candidate keys for the output relation of a relational algebra operator. This property is important for evaluating the precondition of many heuristic rewrite rules applied by GProM, e.g., rules that reduce the number of duplicate removal operators in a query. To complete this work, I provide an experimental evaluation which confirms that this property is extremely useful for improving the performance at game provenance.La procedencia de datos proporciona información sobre el origen de los datos, y ha atraído mucho la atención de la comunidad de investigación en bases de datos. Se ha demostrado que es esencial para una amplia gama de casos, desde debugging de datos y consultas hasta bases de datos probabilísticos. Existen diferentes técnicas para el cálculo de la procedencia de datos de una consulta. Sin embargo, incluso los optimizadores de bases de datos sofisticados suelen ser incapaces de producir un plan de ejecución eficiente para cálculos de procedencia debido a su complejidad inherente y suestructura inusual. A lo largo de este trabajo, desarrollo el módulo para inferir la propiedad clave a los operadores, como parte de las técnicas de optimización heurística para sistemas de procedencia de datos basados en la reescritura para hacer frente al problema de optimización y presentar una implementación de este módulo en el sistema middleware de procedencia GProM. La propiedad clave almacena el conjunto de claves candidatas para la relación de salida de un operador de álgebra relacional. Esta propiedad es importante para evaluar la condición previa de muchas reglas de reescritura heurísticas aplicados por el sistema GProM, por ejemplo, las normas que reducen el número de operadores de eliminación de duplicados en una consulta. Para completar este trabajo, proporciono una evaluación experimental que confirma que esta propiedad es extremadamente útil para mejorar el rendimiento en el juego de procedencia.La procedència de dades proporciona informació sobre l’origen de les dades, i ha atret molt l’atenció de la comunitat de recerca en bases de dades. S’ha demostrat que és essencial per a una àmplia gamma de casos, des de debugging de dades i consultes fins a bases de dades probabilístiques. Existeixen diferents tècniques per al càlcul de la procedència de dades d’una consulta. No obstant això, fins i tot els optimitzadors de bases de dades sofisticats solen ser incapaços de produir un pla d’execució eficient per a càlculs de procedència a causa de la seva complexitat inherent i la seva estructura inusual. Al llarg d’aquest treball, desenvolupo un mòdul per inferir la propietat clau als operadors, com a part de les tècniques d’optimització heurística per a sistemes de procedència de dades basades en la reescriptura per fer front al problema d’optimització i presentar una implementació d’aquest mòdul en el sistema middleware de procedència GProM. La propietat clau emmagatzema el conjunt de claus candidates per a la relació de sortida d’un operador d’àlgebra relacional. Aquesta propietat és important per avaluar la condició prèvia de moltes regles de reescriptura heurístiques aplicats pel sistema GProM, per exemple, les normes que redueixen el nombre d’operadors d’eliminació de duplicats en una consulta. Per completar aquest projecte, proporciono una avaluació experimental que confirma que aquesta propietat és extremadament útil per millorar el rendiment en el joc de procedència

Engineering Enterprise Software Systems with Interactive UML Models and Aspect-Oriented Middleware

Large scale enterprise software systems are inherently complex and hard to maintain. To deal with this complexity, current mainstream software engineering practices aim at raising the level of abstraction to visual models described in OMG’s UML modeling language. Current UML tools, however, produce static design diagrams for documentation which quickly become out-of-sync with the software, and thus obsolete. To address this issue, current model-driven software development approaches aim at software automation using generators that translate models into code. However, these solutions don’t have a good answer for dealing with legacy source code and the evolution of existing enterprise software systems. This research investigates an alternative solution by making the process of modeling more interactive with a simulator and integrating simulation with the live software system. Such an approach supports model-driven development at a higher-level of abstraction with models without sacrificing the need to drop into a lower-level with code. Additionally, simulation also supports better evolution since the impact of a change to a particular area of existing software can be better understood using simulated “what-if” scenarios. This project proposes such a solution by developing a web-based UML simulator for modeling use cases and sequence diagrams and integrating the simulator with existing applications using aspect-oriented middleware technology

Programming Languages and Systems

This open access book constitutes the proceedings of the 30th European Symposium on Programming, ESOP 2021, which was held during March 27 until April 1, 2021, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2021. The conference was planned to take place in Luxembourg and changed to an online format due to the COVID-19 pandemic. The 24 papers included in this volume were carefully reviewed and selected from 79 submissions. They deal with fundamental issues in the specification, design, analysis, and implementation of programming languages and systems

Building on Progress - Expanding the Research Infrastructure for the Social, Economic, and Behavioral Sciences. Vol. 1

The publication provides a comprehensive compendium of the current state of Germany's research infrastructure in the social, economic, and behavioural sciences. In addition, the book presents detailed discussions of the current needs of empirical researchers in these fields and opportunities for future development. The book contains 68 advisory reports by more than 100 internationally recognized authors from a wide range of fields and recommendations by the German Data Forum (RatSWD) on how to improve the research infrastructure so as to create conditions ideal for making Germany's social, economic, and behavioral sciences more innovative and internationally competitive. The German Data Forum (RatSWD) has discussed the broad spectrum of issues covered by these advisory reports extensively, and has developed general recommendations on how to expand the research infrastructure to meet the needs of scholars in the social and economic sciences