ParSEval: Plan-aware Test Database Generation for SQL Equivalence Evaluation
Summary: ParSEval generates SQL test databases using operator semantics and branch coverage over logical-plan execution paths, reducing false positives in equivalence testing. It supports 40% more query pairs than verifiers and finds more inequivalences than prior generators, 21× faster. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Chunyu Chen (Simon Fraser University)
- 2. Zhengjie Miao (Simon Fraser University)
- 3. Yong Zhang (Huawei)
- 4. Jiannan Wang (Huawei; Simon Fraser University)
BibTeX Citation
@article{chen_vldb25,
title = {{ParSEval: Plan-aware Test Database Generation for SQL Equivalence Evaluation}},
author = {Chen, Chunyu and Miao, Zhengjie and Zhang, Yong and Wang, Jiannan},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {11},
pages = {4750--4762},
doi = {10.14778/3749646.3749727},
url = {https://doi.org/10.14778/3749646.3749727},
year = {2025}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,199 | Automated Discovery of Test Oracles for Database Management Systems Using LLMs | 2026 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 16 of 16 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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