Detecting Join Bugs in Database Engines via Join Implication Reasoning
Summary: Join Implication Reasoning (JIR) derives a target join’s oracle from semantically related join results, enabling scalable, predicate-agnostic testing across join types. Evaluated on 11 DBMSs, it exposed 100 unique bugs, including 69 join-logic defects. (summarized by gpt-5.6-luna on Jul 26 2026)
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Authors
- 1. Zhaokun Xiang (National University of Singapore)
- 2. Suyang Zhong (National University of Singapore)
- 3. Manuel Rigger (National University of Singapore)
BibTeX Citation
@inproceedings{xiang_sigmod26,
title = {{Detecting Join Bugs in Database Engines via Join Implication Reasoning}},
author = {Xiang, Zhaokun and Zhong, Suyang and Rigger, Manuel},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3802036},
url = {https://dl.acm.org/doi/10.1145/3802036},
year = {2026}
}
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