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Eina per a la generació de dades de test massives per a bases de dades relacionals

Authors: Maynou Yelamos, Marc;

Eina per a la generació de dades de test massives per a bases de dades relacionals

Abstract

És impossible imaginar el món actual sense sistemes software. La societat actual depèn en gran manera de processos i activitats portades a terme per programari de forma independent. Com a resultat, és essencial assegurar que els diferents mecanismes que defineixen el nostre dia a dia tinguin una implementació adequada que eviti la generació d'errors que podrien causar un gran perjudici. Més concretament, bona part dels programes més importants i estesos de l'actualitat es basen en l'emmagatzematge de grans quantitats de dades. Per tal d'assegurar la correctesa d'aquests sistemes, és necessari generar grans quantitats d'informació que explorin tota la casuística oferida pel disseny que incorporin. Això permet corroborar que el producte és fiable i tindrà el comportament esperat en qualsevol circumstància. Els processos actuals de test de software són, però, llargs, tediosos i amb una alta probabilitat d'introduir errors. Això és degut a la manca d'eines que permetin optimitzar els mecanismes per generar les dades de prova, procés que es realitza manualment. L'objectiu d'aquest treball és, doncs, desenvolupar un sistema que permeti la generació massiva de dades que siguin representatives del disseny d'un determinat programa. Com a resultat, es podran accelerar les fases de test alhora que es generaran sistemes més segurs i fiables.

Country
Spain
Keywords

Bases de dades, Big data, Databases, clonació, instància, :Informàtica [Àrees temàtiques de la UPC], fusió, chase, Dades massives, Àrees temàtiques de la UPC::Informàtica

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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