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

Katerina Tzompanaki (1, 2, 3, 4)

1 LaHDAK - LRI - Données et Connaissances Massives et Hétérogènes (LRI)
2 OAK - Database optimizations and architectures for complex large data
3 UP11 - Université Paris-Sud - Paris 11
4 LRI - Laboratoire de Recherche en Informatique

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.

Domaines: Base de données [cs.DB]; Informatique [cs]

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⟩