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

Katerina Tzompanaki 1, 2, 3, 4, *
* Corresponding author
2 OAK - Database optimizations and architectures for complex large data
Inria Saclay - Ile de France, LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, 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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Submitted on : Monday, December 15, 2014 - 4:34:20 PM
Last modification on : Thursday, July 8, 2021 - 3:48:18 AM
Long-term archiving on: : Monday, March 16, 2015 - 12:21:34 PM


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  • HAL Id : hal-01095488, version 1


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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