SQLess: Dialect-Agnostic SQL Query Simplification-Reference-Cited by-同舟云学术

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SQLess: Dialect-Agnostic SQL Query Simplification

Published:2024-09-11 Issue: Volume:98 Page:743-754
ISSN:
Container-title:Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis
language:
Short-container-title:

Author:

Lin Li¹^ORCID,Hao Zongyin¹^ORCID,Wang Chengpeng²^ORCID,Wang Zhuangda¹^ORCID,Wu Rongxin¹^ORCID,Fan Gang³^ORCID

Affiliation:

1. Xiamen Key Laboratory of Intelligent Storage and Computing, School of Informatics, Xiamen University, Xiamen, China

2. Hong Kong University of Science and Technology, Hong Kong, China

3. Ant Group, Shenzhen, China

Funder

NSFC

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3650212.3680317

Reference51 articles.

1. Alfred V. Aho, Monica S. Lam, Ravi Sethi, and Jeffrey D. Ullman. 2006. Compilers: Principles, Techniques, and Tools (2nd ed.). Pearson Education.

2. ANSI. 2023. The SQL Standard - ISO/IEC 9075:2023 (ANSI X3.135). https://blog.ansi.org/sql-standard-iso-iec-9075-2023-ansi-x3-135/ [Online; accessed 12-Dec-2023]

3. Andrea Arcuri and Lionel C. Briand. 2011. A practical guide for using statistical tests to assess randomized algorithms in software engineering. In Proceedings of the 33rd International Conference on Software Engineering. 1–10.

4. J Asplund. 2011. Data Science revealed: Data-driven glimpse into the burgeoning new field.

5. QAGen

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