Testing Spatial Database Engines via Spatial Equivalent Transformation

Shijie Li, Dongping Wang, Liang Liu, Keyue Yang, Lingwei Kuang. 2025. 2025 4th International Conference on Geographic Information and Remote Sensing Technology (GIRST).

Read the paper · doi:10.1109/girst67753.2025.11382165

What this paper does with SQLancer

SQLancer's oracles are cited collectively as the mature body of logic-bug detection for relational systems, against which the paucity of spatial work is measured. The one existing spatial tool, Spatter, is named separately. Both mentions are reachable only through citation markers, and the paper neither runs nor builds on any SQLancer technique. This work tests spatial database engines by transforming a query into a spatially equivalent one -- applying a transformation that preserves topological relations -- and checking the results agree. Spatial systems have had far less testing attention than relational ones, and the paper notes that only one tool existed for finding logic bugs in them. Written by claude-opus-5 from the 2 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 (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
4	Rigger, M., and Su, Z. Detecting optimization bugs in database engines via NoREC. In Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software E...	sqlancer publication · NOREC
5	Rigger, M., and Su, Z. Finding bugs in database systems via query partitioning. Proc. ACM Program. Lang. 4, OOPSLA(nov 2020).	sqlancer publication · TLP
6	Rigger, M., and Su, Z. Testing database engines via pivoted query synthesis. In Proceedings of the 14th USENIX Conference on Operating Systems Design and Implementation (USA, 2020), OSDI’20, USENIX Association.	sqlancer publication · PQS
8	Jinsheng Ba and Manuel Rigger. 2023. Testing Database Engines via Query Plan Guidance. In Proceedings of the 45th International Conference on Software Engineering (ICSE ’23). IEEE Press, 2060–2071. https://doi.org/10....	sqlancer publication · QPG
10	W. Deng, Q. Mang, C. Zhang, and M. Rigger, “Finding Logic Bugs in Spatial Database Engines via Affine Equivalent Inputs,” 2, no. 6, Art. no. 235, pp. 1–26, Dec. 2024, doi: 10.1145/3698810.	project authored

Every place it refers to SQLancer (2)

2 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	Although crash bug detection [2] [3] and logic bug detection [4] [5] [6] [7] [8] are both mature for RDBMSs, SDBMSs suffer from a relative paucity of studies.	citation marker motivation	I INTRODUCTION page 1
M2	The sole tool for testing logic bugs of SDBMSs, Spatter [10], leverages the affine invariance of topological relations.	citation marker project authored background	I INTRODUCTION page 1

This page is rendered from _data/papers/paper_doi_10_1109_girst67753_2025_11382165.json, extracted from supplied pdf. 5 pages, 16 references parsed.