← Research building on SQLancer

Philipp Reisinger, Daniel Hofer, Bahara Muradi, Josef Küng. 2025. Communications in computer and information science.

Read the paper · doi:10.1007/978-981-95-4721-0_7

What this paper does with SQLancer

SQLancer's techniques appear as part of the body of engine-focused fuzzing the paper positions itself against. Test oracles are cited as the route by which prior work finds logic bugs in database engines, alongside SQL-Smith for crashes and Apollo for performance, and the graph-database tools -- GraphGenie, GRev and others -- are described as providing oracles for a specific engine. That is precisely the boundary CypherFuzzer steps outside: correctness of results given a privilege set, not correctness of results as such. CypherFuzzer tests access control in graph databases rather than query evaluation: it generates Cypher queries under different user privileges and checks that results respect the permissions granted. Its premise is that existing graph-database fuzzing has targeted the engine itself and left the authorization layer untested. Written by claude-opus-5 from the 5 places this paper refers to SQLancer. The quotations below are the paper's own words, stored verbatim when the text was extracted.

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 (3)

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.

#EntryMatched as
10 Jiang, Y., Liu, J., Ba, J., Yap, R.H.C., Liang, Z., Rigger, M.: Detecting logic bugs in graph database management systems via injective and surjective graph query transformation. In: Proceedings of the IEEE/ACM 46th I... project authored
13 Kamm, M., Rigger, M., Zhang, C., Su, Z.: Testing graph database engines via query partitioning. In: Proceedings of the 32nd ACMSIGSOFT International Symposium on Software Testing and Analysis, ISSTA 2023, pp. 140–149.... project authored
21 Rigger, M., Su, Z.: Finding bugs in database systems via query partitioning. Pro c. ACM Program. Lang.4(OOPSLA) (2020). https:// doi.org/10.1145/3428279 sqlancer publication · TLP

Every place it refers to SQLancer (5)

5 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 Previous work with regard to fuzzing primarily focused on testing the graph database engine itself [ 5, 8,10,14,15,20,25]. citation marker project authored
motivation 		1 Introduction
page 2
M2 – Grave de Peralta Gonzalez [ 20] extended GraphGenie [ 10] with a tool for testing Cypher subqueries. citation marker project authored
background 		2.2 Fuzzing Cypher Queries
page 4
M3 , SQL-Smith [ 23], Squirrel [ 28]), logic bugs (through test oracles [ 21]), and performance issues (Apollo [ 12]) in database engines. citation marker
definition 		3 Related Work
page 5
M4 However, in the context of graph databases, existing efforts to fuzzing Cypher or similar query languages only focused on testing the graph database engineitself [ 8,10,13– 15,25,27,29] (some of which were discussed in Sect. citation marker project authored
motivation 		3 Related Work
page 6
M5 Thus, these tools prov ide test oracles for a specific graphdatabase engine [ 10,13– 15,29], where GRev [ 15] further leverages test oracles to detect shared bugs across multiple GDBMS through equivalent query rewriting. citation marker project authored
definition 		3 Related Work
page 6

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