Semantic Conformance Testing of Relational DBMS
Shuang Liu, Chenglin Tian, Jun Sun, Ruifeng Wang, Wei Lu, Yongxin Zhao, Yinxing Xue, Junjie Wang, Xiaoyong Du
Abstract
Relational DBMS implementations are expected to adhere to SQL standards. However, there are currently no tools available that can automatically verify this conformance. The main reasons are twofold. First, the SQL standard specification, documented in natural language, tends to be ambiguous and is not directly executable. Second, it is difficult to generate test queries that thoroughly cover all aspects, e.g., keywords and parameters, defined in the SQL specification. In this work, we introduce the first method for semantic conformance testing of RDBMSs. Our contributions are threefold. Firstly, we formally define the denotational semantics of SQL and implement them in Prolog, creating an executable reference RDBMS for differential testing against existing RDBMSs. Secondly, we propose three coverage criteria based on these formal semantics, along with a coverage-guided query generation algorithm that effectively generates queries achieving high semantic coverage. Lastly, we apply our approach to six widely-used and thoroughly tested RDBMSs, e.g., MySQL, PostgreSQL and OceanBase, uncovering 19 bugs and 13 inconsistencies, all of which are confirmed by RDBMS developers.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 5047d25d-ecd0-406d-b7bb-08eae8870c2cCited by top-tier papers1
Ask how each one uses itBuilds on8
- Testing Database Engines via Pivoted Query SynthesisManuel Rigger, Zhendong SuOSDI 2020 · 150 citations
- Finding bugs in database systems via query partitioningManuel Rigger, Zhendong SuOOPSLA 2020 · 116 citations
- Detecting optimization bugs in database engines via non-optimizing reference engine constructionManuel Rigger, Zhendong SuFSE 2020 · 104 citations
- Semantic Understanding of Smart Contracts: Executable Operational Semantics of SolidityJiao Jiao, Shuanglong Kan, Shang-Wei Lin, David Sanán et al.S&P 2020 · 82 citations
- APOLLO: Automatic Detection and Diagnosis of Performance Regressions in Database SystemsJinho Jung, Hong Hu, Joy Arulraj, Taesoo Kim et al.VLDB 2020 · 77 citations
Related papers
- Pinolo: Detecting Logical Bugs in Database Management Systems with Approximate Query SynthesisZongyin Hao, Quanfeng Huang, Chengpeng Wang, Jianfeng Wang et al.USENIX ATC 2023 · 26 citations
- Systematically Cover SQL Syntactic Structures via 𝑘-SequenceHongtao Zhou, Yingying Zheng, Yu Gao, Jiansen Song et al.ISSTA 2026 · 1 citation
- LLMSQLMUTATOR: LLM-Powered Test Case Generation for Database Using Bug ReportsChenglin Tian, Chaofan Li, Yawen Li, Yingxia ShaoICDE 2026
- One DBMS, Two Modes, and a Bunch of Bugs: Catching Logic Bugs in Distributed DBMSs via Differential TestingZi-Xuan Fu, Jia-Ju Bai, Hong-Bo Feng, Kang ChenSIGMOD 2026
- Scaling Automated Database System TestingSuyang Zhong, Manuel RiggerASPLOS 2026 · 4 citations
