Guardrail: Automated Integrity Constraint Synthesis From Noisy Data

Summary: Guardrail expresses integrity constraints as programs in a DSL that can be synthesized robustly from noisy data to detect and repair errors beyond classical FDs. Its synthesis algorithm uses statistical structural priors to sketch and prune search, yielding ~87% error reduction on ML‑augmented SQL across real datasets (open-source). (summarized by gpt-5-mini on Feb 11 2026)

Paper ID: 7513
Venue: SIGMOD
Year: 2026
Pagerank: 5.093636e-05
Overall Rank: 10,317 | 29.22%
DOI: 10.1145/3749166

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Authors

1. Pingchuan Ma (Hong Kong University of Science and Technology)
2. Zhaoyu Wang (Hong Kong University of Science and Technology)
3. Zhenlan Ji (Hong Kong University of Science and Technology)
4. Zongjie Li (Hong Kong University of Science and Technology)
5. Ao Sun (Hong Kong University of Science and Technology)
6. Shuai Wang (Hong Kong University of Science and Technology)

BibTeX Citation

@inproceedings{ma_sigmod26,
        title = {{Guardrail: Automated Integrity Constraint Synthesis From Noisy Data}},
        author = {Ma, Pingchuan and Wang, Zhaoyu and Ji, Zhenlan and Li, Zongjie and Sun, Ao and Wang, Shuai},
        series = {{SIGMOD} '26},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3749166},
        url = {https://dl.acm.org/doi/10.1145/3749166},
        year = {2026}
}

Incoming Citations (Sorted by Pagerank)

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Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 20 of 20 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
142	LOF: Identifying Density-Based Local Outliers	2000	SIGMOD	0.0002962566
159	CORDS: Automatic Discovery of Correlations and Soft Functional Dependencies	2004	SIGMOD	0.00028129426
376	Discovering Denial Constraints	2013	VLDB	0.00019677674
432	Mining Database Structure; Or, How to Build a Data Quality Browser	2002	SIGMOD	0.00018572055
693	Algorithms for Mining Distance-Based Outliers in Large Datasets	1998	VLDB	0.00014918477
729	Functional Dependency Discovery: An Experimental Evaluation of Seven Algorithms	2015	VLDB	0.00014539421
800	The LLUNATIC Data-Cleaning Framework	2013	VLDB	0.00013911223
1,165	Foofah: Transforming Data By Example	2017	SIGMOD	0.00011860616
2,041	Combining Quantitative and Logical Data Cleaning	2016	VLDB	9.2692538e-05
2,142	Messing Up with BART: Error Generation for Evaluating Data-Cleaning Algorithms	2016	VLDB	9.0975882e-05
2,584	Complaint-driven Training Data Debugging for Query 2.0	2020	SIGMOD	8.3783546e-05
2,728	Uni-Detect: A Unified Approach to Automated Error Detection in Tables	2019	SIGMOD	8.1995954e-05
2,981	Towards Dependable Data Repairing with Fixing Rules	2014	SIGMOD	7.8960114e-05
3,004	SCODED: Statistical Constraint Oriented Data Error Detection	2020	SIGMOD	7.8608629e-05
3,441	A Statistical Perspective on Discovering Functional Dependencies in Noisy Data	2020	SIGMOD	7.4138323e-05
6,664	On Multiple Semantics for Declarative Database Repairs	2020	SIGMOD	5.8090585e-05
7,397	Conformance Constraint Discovery: Measuring Trust in Data-Driven Systems	2021	SIGMOD	5.6256632e-05
7,690	Auto-Validate: Unsupervised Data Validation Using Data-Domain Patterns Inferred from Data Lakes	2021	SIGMOD	5.5669307e-05
8,838	The Cost of Representation by Subset Repairs	2025	VLDB	5.3592132e-05
9,020	Data-Driven Insight Synthesis for Multi-Dimensional Data	2024	VLDB	5.3306775e-05

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