Randomized Differential Testing of RDF Stores
Read the paper · doi:10.1109/icse-companion58688.2023.00041
What this paper does with SQLancer
SQLancer's techniques appear as the relational precedent the paper places itself after. TLP, NoREC, PQS and DQE are named together as the oracles developed for relational systems that have found many bugs there, and GDBMeter as the tool that carried query partitioning into property-graph databases. The paper's own contribution is differential testing across RDF stores, so the citation establishes the lineage rather than a technical relationship.
A short paper on randomized differential testing for RDF stores, which use SPARQL and the RDF data model rather than the labeled property graph model the existing graph testers target. It runs the same query across several RDF stores and reports disagreements, extending automated logic-bug detection to a data model that had none.
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 (5)
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 |
|---|---|---|
| 13 | M. Kamm, M. Rigger, C. Zhang, and Z. Su, “Testing graph database engines via query partitioning,” in Proceedings of ACMSIGSOFT International Symposium on Software Testing and Analysis (ISSTA), 2023. | project authored |
| 15 | M. Rigger and Z. Su, “Finding bugs in database systems via query partitioning,” Proceedings of the ACM on Programming Languages, vol. 4, no. OOPSLA, 2020. | sqlancer publication · TLP |
| 16 | ——, “Detecting optimization bugs in database engines via nonoptimizing reference engine construction,” in Proceedings of ACM Joint European Software Engineering Conference and Symposium on the F oundations of Software... | sqlancer publication · NOREC |
| 17 | ——, “Testing database engines via pivoted query synthesis,” in Proceedings of USENIX Symposium on Operating Systems Design and Implementation (OSDI), 2020, pp. 667–682. | sqlancer publication · PQS |
| 25 | J. Ba and M. Rigger, “Testing database engines via query plan guidance,” inProceedings of International Conference on Software Engineering (ICSE), 2023. | sqlancer publication · QPG |
Every place it refers to SQLancer (7)
7 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 | Similar to other GDBs that are built on the labeled property graph model [11]–[13] and relational database systems (RDBMSs) [14]–[18], incorrect implementations of RDF stores can introduce logic bugs that result in an incorrect query result for a given SPARQL query, e. |
citation marker project authored |
I INTRODUCTION page 1 |
| M2 | , Grand [11], GDsmith [12] and GDBMeter [13], detect logic bugs in Gremlin-based or Cypher-based GDBs, which adopt the labeled property graph model. |
citation marker project authored |
I INTRODUCTION page 1 |
| M3 | Existing RDBMS testing approaches [14]–[20] detect bugs in RDBMSs. |
citation marker |
I INTRODUCTION page 1 |
| M4 | Some approaches [11]–[13], [23] are proposed to test GDBs. |
citation marker project authored |
VI RELA TED WORK page 4 |
| M5 | GDBMeter [13] adopts metamorphic testing by partitioning a given query into three derived sub-queries to test GDBs. |
citation marker project authored |
VI RELA TED WORK page 4 |
| M6 | Many approaches [14]–[20], [25]–[33] are proposed to find bugs in RDBMSs that use SQL as a standardized query language. |
citation marker |
VI RELA TED WORK page 4 |
| M7 | TLP [15], NoREC [16], PQS [17] and DQE [18] develop various test oracles to detect logic bugs and optimization bugs, and have found many bugs in popular RDBMSs. |
technique |
VI RELA TED WORK page 4 |