DAFuzz: data-aware fuzzing of in-memory data stores
Read the paper · doi:10.7717/peerj-cs.1592
What this paper does with SQLancer
SQLancer appears in the related-work survey in the ACM author-year style, so none of the three mentions names it directly -- they are reachable only through the citation. It is grouped with SQLsmith as a black-box fuzzer for SQL databases, cited again as an example of fuzzers that ensure statements are semantically valid, which is the property DAFuzz pursues for data-structure commands, and a third time as work targeting logic bugs rather than crashes or assertion failures.
DAFuzz fuzzes in-memory data stores such as Redis, whose commands operate on typed data structures. Feeding a command arguments of the wrong type gets it rejected immediately, so DAFuzz tracks the types of live data and generates commands whose arguments match, reaching code that type-blind fuzzing does not.
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.
Every place it refers to SQLancer (3)
3 sentences, 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 | 1592 20/26 related program is SQL database, and different special black-box fuzzers ( Seltenreich, Tang & Mullender, 2022 ;Guo, 2017 ;Rigger, 2023 ;Rigger & Su, 2020 ) and grey-box fuzzers (Zhong et al. |
author year citation |
page 20 |
| M2 | Recently, fuzzers also try to ensure the statements are semantically valid ( Rigger, 2023 ;Rigger & Su, 2020 ;Zhong et al. |
author year citation |
page 21 |
| M3 | Several recent pieces of research focus on detecting logic bugs but not traditional crashes or assert failures ( Rigger, 2023 ;Rigger & Su, 2020 ;Liang, Liu & Hu, 2022 ). |
author year citation |
page 21 |