Nabil: A Text-to-SQL Model Based on Brain-Inspired Computing Techniques and Large Language Modeling
Read the paper · doi:10.3390/electronics14193910
What this paper does with SQLancer
How it was classified
uses infrastructure — no
SQLancer is cited as related work; no reuse of its code, generator or workload is described.
extends technique — no
No SQLancer technique is extended; the citation is background.
compares with — no
No empirical comparison against SQLancer or one of its oracles is reported.
describes as state of the art — no
The text does not describe 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 |
|---|---|---|
| 20 | Ba, J.; Rigger, M. Testing database engines via query plan guidance. In Proceedings of the 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE), Melbourne, Australia, 14–20 May 2023; IEEE: New Yo... | 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 | proposed query plan guidance (QPG) to fully automatically test errors in database systems and applied it to three database systems: SQLite, TiDB, and CockroachDB [ 20]. |
technique |
2 Related Works page 4 |