Detecting Logical Bugs of DBMS with Coverage-based Guidance

Yu Liang, Song Liu, Hong Hu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Database management systems (DBMSs) are critical components of modern data-intensive applications. Developers have adopted many testing techniques to detect DBMS bugs such as crashes and assertion failures. However, most previous efforts cannot detect logical bugs that make the DBMS return incorrect results. Recent work proposed several oracles to identify incorrect results, but they rely on rule-based expression generation to synthesize queries without any guidance. In this paper, we propose to combine coverage-based guidance, validity-oriented mutations and oracles to detect logical bugs in DBMS systems. Specifically, we first design a set of general APIs to decouple the logic of fuzzers and oracles, so that developers can easily port fuzzing tools to test DBMSs and write new oracles for existing fuzzers. Then, we provide validity-oriented mutations to generate high-quality query statements in order to find more logical bugs. Our prototype, SQLRight, outperforms existing tools that only rely on oracles or code coverage. In total, SQLRight detects 18 logical bugs from two well-tested DBMSs, SQLite and MySQL. All bugs have been confirmed and 14 of them have been fixed.

Original languageEnglish (US)
Title of host publicationProceedings of the 31st USENIX Security Symposium, Security 2022
PublisherUSENIX Association
Pages4309-4326
Number of pages18
ISBN (Electronic)9781939133311
StatePublished - 2022
Event31st USENIX Security Symposium, Security 2022 - Boston, United States
Duration: Aug 10 2022Aug 12 2022

Publication series

NameProceedings of the 31st USENIX Security Symposium, Security 2022

Conference

Conference31st USENIX Security Symposium, Security 2022
Country/TerritoryUnited States
CityBoston
Period8/10/228/12/22

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems
  • Safety, Risk, Reliability and Quality

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