Relational Query Synthesis ⋈ Decision Tree Learning
Summary: Interleaves search-based SPJ synthesis (for joins/projections) with decision-tree learning (for categorical and numeric comparison predicates) to get a complete, minimality-encouraging relational query synthesizer. LIBRA solves 1,361/1,475 benchmark instances (avg 59s) and outperforms Scythe and PatSQL. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Aaditya Naik
- 2. Aalok Thakkar
- 3. Adam Stein
- 4. Rajeev Alur
- 5. Mayur Naik
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Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 901 | To Join or Not to Join? Thinking Twice about Joins before Feature Selection | 2016 | SIGMOD | 0.00015462938 |
| 973 | Natural language to SQL: Where are we today? | 2020 | VLDB | 0.0001488435 |
| 1,421 | Duoquest: A Dual-Specification System for Expressive SQL Queries | 2020 | SIGMOD | 0.00012052759 |
| 1,462 | ARDA: Automatic Relational Data Augmentation for Machine Learning | 2020 | VLDB | 0.00011866333 |
| 3,349 | QuickFOIL: Scalable Inductive Logic Programming | 2015 | VLDB | 7.1889581e-05 |
| 3,604 | The Relational Model Of Data And Cylindrical Algebras | 1982 | PODS | 6.9261753e-05 |
| 4,982 | Interactive Query Synthesis from Input-Output Examples | 2017 | SIGMOD | 5.7817493e-05 |
| 5,554 | PATSQL: Efficient Synthesis of SQL Queries from Example Tables with Quick Inference of Projected Columns | 2021 | VLDB | 5.4410603e-05 |
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