Interactive Demonstration of SQLCheck
Summary: SQLCheck automatically detects SQL anti-patterns, ranks them by performance, maintainability, and accuracy impact, and proposes query/schema fixes. Its demonstration showcases high-accuracy analysis and prevalence across large open-source query and database collections. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Arthita Ghosh (Georgia Institute of Technology)
- 2. Deven Bansod (Georgia Institute of Technology; Meta)
- 3. Arpit Narechania (Georgia Institute of Technology)
- 4. Prashanth Dintyala (Georgia Institute of Technology; NVIDIA)
- 5. Su Timurturkan (Georgia Institute of Technology)
- 6. Joy Arulraj (Georgia Institute of Technology)
BibTeX Citation
@article{ghosh_vldb21,
title = {{Interactive Demonstration of SQLCheck}},
author = {Ghosh, Arthita and Bansod, Deven and Narechania, Arpit and Dintyala, Prashanth and Timurturkan, Su and Arulraj, Joy},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {12},
pages = {2779--2782},
doi = {10.14778/3476311.3476343},
url = {https://doi.org/10.14778/3476311.3476343},
year = {2021}
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 641 | Relational Cloud: A Database-as-a-Service for the Cloud | 2011 | CIDR | 0.00015400863 |
| 1,000 | Unbundling Transaction Services in the Cloud | 2009 | CIDR | 0.000127281 |
| 2,154 | Leveraging Lock Contention to Improve OLTP Application Performance | 2016 | VLDB | 9.0745745e-05 |
| 2,930 | StatusQuo: Making Familiar Abstractions Perform Using Program Analysis | 2013 | CIDR | 7.9494635e-05 |
| 4,082 | SQLCheck: Automated Detection and Diagnosis of SQL Anti-Patterns | 2020 | SIGMOD | 6.9164719e-05 |
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