Understanding Query Optimization Bugs in Graph Database Systems
Read the paper · doi:10.1145/3779212.3790244
What this paper does with SQLancer
The comparison here is against the graph-database descendants of SQLancer's techniques rather than SQLancer itself: GDsmith, GAMERA, GRev, GraspDB, GraphGenie and Gslicer are the seven state-of-the-art techniques the tool is measured against, several of them built on metamorphic testing and several co-authored by SQLancer's authors. SQLancer's own work is cited for the cost-estimation class of optimization bug and for the 24-hour evaluation methodology.
A characteristic study of query optimization bugs in graph database systems, covering root causes, how the bugs manifest and how they are fixed, from which the authors draw ten findings. Building on the study they developed a testing tool aimed specifically at graph query optimization, which found 20 unique bugs, 10 of them optimization bugs.
How it was classified
uses infrastructure — no
SQLancer is cited, not used; nothing in the mentions describes reusing its code.
extends technique — no
No technique is extended; the citation is background.
compares with — uncertain
The seven tools compared against are graph-database testing techniques, some derived from SQLancer's oracles, but no mention read shows SQLancer itself being run.
describes as state of the art — no
The citation does not characterise SQLancer as the state of the art.
SQLancer publications it cites (6)
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 |
|---|---|---|
| 11 | Jinsheng Ba and Manuel Rigger. 2023. Testing Database Engines via Query Plan Guidance. In on Software Engineering (ICSE). 2060–2071. doi:10.1109/ICSE48619. 2023.00174 | sqlancer publication · QPG |
| 20 | Yuancheng Jiang, Jiahao Liu, Jinsheng Ba, Roland H. C. Yap, Zhenkai Liang, and Manuel Rigger. 2024. Detecting Logic Bugs in Graph Database Management Systems via Injective and Surjective Graph Query Transformation. In... | project authored |
| 21 | Zu-Ming Jiang, Si Liu, Manuel Rigger, and Zhendong Su. 2023. Detecting Transactional Bugs in Database Engines via Graph-Based Oracle Construction. In 17th USENIX Symposium on Operating Systems Design and Implementatio... | project authored |
| 35 | Qiuyang Mang, Jinsheng Ba, Pinjia He, and Manuel Rigger. 2025. Finding Logic Bugs in Graph-processing Systems via Graph-cutting. doi:10.1145/3725300 | project authored |
| 45 | Manuel Rigger and Zhendong Su. 2020. Detecting optimization bugs in database engines via non-optimizing reference engine construction. InProceedings of the 28th ACM Joint Meeting on European Software Engineering Confe... | sqlancer publication · NOREC |
| 46 | Manuel Rigger and Zhendong Su. 2020. Testing database engines via pivoted query synthesis. In Proceedings of the 14th USENIX Conference on Operating Systems Design and Implementation (OSDI’20). USENIX Association, USA... | sqlancer publication · PQS |
Every place it refers to SQLancer (11)
11 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 | Indeed, recent years have witnessed a surge of research efforts for testing GDBMSs [18,32,35,36]. |
citation marker project authored |
1 Introduction page 1 |
| M2 | GRev [36], GraspDB [ 32], and Gslicer [ 35] are the representative GDBMS testing techniques that are built on top of MT. |
citation marker project authored |
1 Introduction page 1 |
| M3 | For optimization bugs due to inaccurate cost estimations or defective plan space exploration algorithms, previous works on DBMS testing [ 11,21,45,46] also frequently report them. |
citation marker |
4.4 Discussion: Query optimization bugs in GDBMS page 8 |
| M4 | However, most existing GDBMS testing techniques do not support the subquery clause kind at all, including GDSmith [ 18], GAMERA [ 75], GraspDB [ 32], GRev [ 36], Gslicer [35], and GQS [ 62]). |
citation marker project authored |
5.2.1 Clause skeleton. page 9 |
| M5 | Although GraphGenie [ 20] supports the kind of subquery clause, it only supports the CALL{} clause. |
citation marker project authored |
5.2.1 Clause skeleton. page 9 |
| M6 | Like the typical methodology used to evaluate the effectiveness of database testing methods [ 21,45,46], the testing process is intermittent and we continuously improved the tool during the process. |
citation marker |
7.2 Evaluation Setup page 12 |
| M7 | 4 Comparison with State of the Art We compare our tool with 7 state-of-the-art GDBMS testing techniques, including GDSmith [ 18], GAMERA [ 75], GraspDB [ 32], GRev [ 36], GraphGenie [ 20], GSlicer [ 35], and GQS [62]. |
citation marker project authored |
7.4 Comparison with State of the Art page 13 |
| M8 | Note that 24-Hour empirical testing is widely used by existing works to compare the effectiveness of different testing techniques [ 35,46,62]. |
citation marker |
7.4.1 Study of Missed Bugs. We first show that our tool page 14 |
| M9 | For the other metamorphic testing techniques, the false alarms are mainly due to the inaccurate transformation rules as also reported by previous studies [32,35], particularly due to the ignorance of constraints on graph entities and the inadequate consideration of special error cases (e. | citation marker project authored | 7.4.1 Study of Missed Bugs. We first show that our tool page 14 |
| M10 | In particular, significant recent efforts have been devoted to testing GDBMSs [ 18,35,36,75]. | citation marker project authored | 7.5.2 Future Work. page 15 |
| M11 | GRev [ 36], Gamera [ 75], GraspDB [ 32], and Gslicer [ 35] are representative techniques built on top of MT. | citation marker project authored | 7.5.2 Future Work. page 15 |