Massive Stochastic Testing of SQL
Summary: RAGS stochastically generates valid SQL statements to stress-test DBMSs, greatly expanding the SQL input domain beyond manual testing. It achieves a million-fold speedup over human generation and execution, enabling scalable, massive workload-based reliability evaluation. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Don Slutz
Incoming Citations (Sorted by Pagerank)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,207 | SQLStorm: Taking Database Benchmarking into the LLM Era | 2025 | VLDB | 4.5583637e-05 |
| 145 | Quickly Generating Billion-Record Synthetic Databases | 1994 | SIGMOD | 0.0004138408 |
| 5,353 | An In-Depth Benchmarking of Text-to-SQL Systems | 2021 | SIGMOD | 5.5521332e-05 |
| 11,576 | RASQL: A Powerful Language and its System for Big Data Applications | 2020 | SIGMOD | 4.1945683e-05 |
| 2,277 | Generating Targeted Queries for Database Testing | 2008 | SIGMOD | 9.1241198e-05 |
| 8,705 | Stochastic Package Queries in Probabilistic Databases | 2020 | SIGMOD | 4.4646588e-05 |
| 888 | QAGen: Generating Query-Aware Test Databases | 2007 | SIGMOD | 0.00015578618 |
| 3,560 | Counting, Enumerating, and Sampling of Execution Plans in a Cost-Based Query Optimizer | 2000 | SIGMOD | 6.9723858e-05 |
| 10,118 | Test Data Generation for Complex SQL Queries | 2026 | SIGMOD | 4.1945683e-05 |
| 4,644 | A genetic approach for random testing of database systems | 2007 | VLDB | 6.0259936e-05 |