Automated Discovery of Test Oracles for Database Management Systems Using LLMs
Summary: Argus uses LLMs to synthesize equivalent-query skeletons, formally checked by a SQL equivalence solver, then instantiates them into reusable DBMS tests. Evaluation across five systems found 41 new bugs, including 36 logic bugs. (summarized by gpt-5.6-luna on Jul 26 2026)
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Authors
- 1. Qiuyang Mang (University of California Berkeley)
- 2. Runyuan He (University of California Berkeley)
- 3. Suyang Zhong (National University of Singapore)
- 4. Xiaoxuan Liu (University of California Berkeley)
- 5. Huanchen Zhang (Tsinghua University)
- 6. Alvin Cheung (University of California Berkeley)
BibTeX Citation
@inproceedings{mang_sigmod26,
title = {{Automated Discovery of Test Oracles for Database Management Systems Using LLMs}},
author = {Mang, Qiuyang and He, Runyuan and Zhong, Suyang and Liu, Xiaoxuan and Zhang, Huanchen and Cheung, Alvin},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3802017},
url = {https://dl.acm.org/doi/10.1145/3802017},
year = {2026}
}
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,382 | Automated Database Testing via LLM-Synthesized SQL Features | 2027 | SIGMOD | 4.9605343e-05 |
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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