Semi-automatic SQL Debugging and Fixing to solve the Missing-Answers Problem

Katerina Tzompanaki 1, 2, 3, 4, *
* Auteur correspondant
2 OAK - Database optimizations and architectures for complex large data
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
Abstract : Asking questions is the driving force for scientific progress. But as important as it is to ask questions, so important is to be able to understand the obtained answers. In this way, we are able to verify the sanity of the question itself and if necessary refine it. In the same spirit, in this PhD we focus on SQL queries over re-lational databases with the aim to (1) pinpoint the reasons on the SQL query that led to missing-answers (tuples that were expected but not obtained in the query result), (2) fix the SQL query so that it best fits the user's expectations, and (3) do both efficiently so as to be of practical use.
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Communication dans un congrès
Very Large Databases (VLDB'14) PhD Workshop, Sep 2014, Hangzhou, China
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Contributeur : Aikaterini Tzompanaki <>
Soumis le : lundi 15 décembre 2014 - 16:34:20
Dernière modification le : lundi 28 mai 2018 - 14:38:02
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Katerina Tzompanaki. Semi-automatic SQL Debugging and Fixing to solve the Missing-Answers Problem. Very Large Databases (VLDB'14) PhD Workshop, Sep 2014, Hangzhou, China. 〈hal-01095488〉

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