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Automatic Generation of SQL Queries.

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Bibliographische Detailangaben
Titel: Automatic Generation of SQL Queries.
Autoren: Quan Do, Agrawal, Rajeev K., Rao, Dhana, Gudivada, Venkat N.
Quelle: Proceedings of the ASEE Annual Conference & Exposition; 2014, p1-11, 11p
Schlagwörter: SQL, ANSI standards, QUERY languages (Computer science), DEEP learning, METADATA
Firma/Körperschaft: INTERNATIONAL Organization for Standardization
Abstract: Structured Query Language (SQL) is an ANSI and ISO standard declarative query language for querying and manipulating relational databases. It is easy to write SQL queries but very difficult to validate them. Often students conclude that a SQL query is correct simply because the query compiles, executes, and fetches data. Therefore, it is crucial that SQL assessment tasks are carefully designed and implemented to ensure a deep learning experience for students. In this paper, we propose an approach to automatically generate SQL queries for assessing students' SQL learning. SQL concepts are modeled using RDFS. The user can select SQL concepts to be included in an assessment and our approach will generate appropriate queries. The proposed approach is generic and is database metadata driven. A Web-based prototype system is developed to illustrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]
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Datenbank: Complementary Index
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Abstract:Structured Query Language (SQL) is an ANSI and ISO standard declarative query language for querying and manipulating relational databases. It is easy to write SQL queries but very difficult to validate them. Often students conclude that a SQL query is correct simply because the query compiles, executes, and fetches data. Therefore, it is crucial that SQL assessment tasks are carefully designed and implemented to ensure a deep learning experience for students. In this paper, we propose an approach to automatically generate SQL queries for assessing students' SQL learning. SQL concepts are modeled using RDFS. The user can select SQL concepts to be included in an assessment and our approach will generate appropriate queries. The proposed approach is generic and is database metadata driven. A Web-based prototype system is developed to illustrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]
ISSN:21535868