Aurora DSQL: Scalable, Multi-Region OLTP
Read the paper · arXiv:2607.13276
What this paper does with SQLancer
How it was classified
uses infrastructure — uncertain (unclear)
M1 says the fuzz-testing approach builds on the approach of SQLancer and generates millions of statements run against DSQL and a reference. Whether AWS runs SQLancer's code or reimplemented its approach is not settled by the mention.
The fuzz-testing approach, building on the approach of SQLancer [ 4], generates millions of example SQL statements and runs them both on DSQL and on AuroraPostgreSQL.
extends technique — no
No technique is extended; the citation is background.
compares with — no
No empirical comparison against SQLancer is reported in the mentions.
describes as state of the art — no
The citation does not characterise SQLancer as the state of the art.
SQLancer publications it cites (1)
Bibliography entries that resolved to a SQLancer publication, or to a paper by one of the project's authors. A sentence citing one of these numbers is a reference to SQLancer even when it never writes the name.
| # | Entry | Matched as |
|---|---|---|
| 4 | Jinsheng Ba and Manuel Rigger. 2023. Testing database engines via query plan guidance. In (ICSE). IEEE, 2060–2071. | sqlancer publication · QPG |
Every place it refers to SQLancer (1)
1 sentence, each stored verbatim from the extracted text with where it was found and how. “Citation marker” means the sentence names no tool at all and was reached through a reference number that resolved to a SQLancer publication.
| Id | Sentence | Found by | Where |
|---|---|---|---|
| M1 | The fuzz-testing approach, building on the approach of SQLancer [ 4], generates millions of example SQL statements and runs them both on DSQL and on AuroraPostgreSQL. |
name |
5.6 Effects of Clock Skew page 10 |