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SQLCheck: Automated Detection and Diagnosis of SQL Anti-Patterns

Summary: SQLCheck automates detection and diagnosis of SQL anti-patterns by combining query analysis with data analysis for high precision. It ranks anti-patterns by impact on performance, maintainability, and accuracy, and suggests rule-based fixes, validated on large open-source query corpora. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6031
Venue
SIGMOD
Year
2020
Pagerank
6.9164719e-05
Overall Rank
4,082 | 72.00%
DOI
10.1145/3318464.3389754

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{dintyala_sigmod20,
        title = {{SQLCheck: Automated Detection and Diagnosis of SQL Anti-Patterns}},
        author = {Dintyala, Prashanth and Narechania, Arpit and Arulraj, Joy},
        series = {{SIGMOD} '20},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3318464.3389754},
        url = {https://dl.acm.org/doi/10.1145/3318464.3389754},
        year = {2020}
}

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