Constraint-based Explanation and Repair of Filter-based Transformations
Summary: Constraint-based explain-and-repair for filter-based transformations; interactive constraints guide generation and explain failures. Emeril prototype demonstrates the approach; achieves 34% more solutions and 77% faster than prior SOTA on synthetic and real datasets. (summarized by gpt-5-nano on Feb 09 2026)
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 107 | WebTables: Exploring the Power of Tables on the Web | 2008 | VLDB | 0.00048377684 |
| 487 | Why Not? | 2009 | SIGMOD | 0.00022050218 |
| 652 | On the Provenance of Non-Answers to Queries over Extracted Data | 2008 | VLDB | 0.00018634477 |
| 1,009 | SnipSuggest: Context-Aware Autocompletion for SQL | 2011 | VLDB | 0.00014653644 |
| 1,125 | How to ConQueR Why-Not Questions | 2010 | SIGMOD | 0.00013845652 |
| 1,267 | Foofah: Transforming Data By Example | 2017 | SIGMOD | 0.00012936483 |
| 1,371 | Tiresias: The Database Oracle for How-To Queries | 2012 | SIGMOD | 0.00012323502 |
| 3,218 | Reverse Data Management | 2011 | VLDB | 7.3592173e-05 |
| 7,577 | Senbazuru: A Prototype Spreadsheet Database Management System | 2013 | VLDB | 4.7064086e-05 |
| 11,796 | A Declarative Query Processing System for Nowcasting | 2017 | VLDB | 4.1945683e-05 |
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