Automatic SQL query generation
Author
Arbabifard, Kamyar
Abstract
Automatic generation of questions for learning assessment has been an area of research interest for long. The advent of Massive Open Online Courses (MOOCs) as well as the goal of providing immediate contextualized feedback to enhance student learning has created renewed interest in automatic question generation. This thesis motivates the automatic question generation problem, gives an overview of the current approaches, and describes the proposed novel approach to automatic generation of SQL queries using the notion of grammar graph.
Subject
Date
2017-07-19
Citation:
APA:
Arbabifard, Kamyar.
(July 2017).
Automatic SQL query generation
(Master's Thesis, East Carolina University). Retrieved from the Scholarship.
(http://hdl.handle.net/10342/6401.)
MLA:
Arbabifard, Kamyar.
Automatic SQL query generation.
Master's Thesis. East Carolina University,
July 2017. The Scholarship.
http://hdl.handle.net/10342/6401.
September 27, 2023.
Chicago:
Arbabifard, Kamyar,
“Automatic SQL query generation”
(Master's Thesis., East Carolina University,
July 2017).
AMA:
Arbabifard, Kamyar.
Automatic SQL query generation
[Master's Thesis]. Greenville, NC: East Carolina University;
July 2017.
Collections
Publisher
East Carolina University