Testing Database Engines via Pivoted Query Synthesis


Manuel Rigger and Zhendong Su, ETH Zurich

Distinguished Artifact Award Winner


Database Management Systems (DBMSs) are used widely, and have been extensively tested by fuzzers, which are successful in finding crash bugs. However, approaches to finding logic bugs, such as when a DBMS computes an incorrect result set, have remained mostly untackled. To this end, we devised a novel and general approach that we have termed Pivoted Query Synthesis. The core idea of this approach is to automatically generate queries for which we ensure that they fetch a specific, randomly selected row, called the pivot row. If the DBMS fails to fetch the pivot row, the likely cause is a bug in the DBMS. We tested our approach on three widely-used and mature DBMSs, namely SQLite, MySQL, and PostgreSQL. In total, we found 121 unique bugs in these DBMSs, 96 of which have been fixed or verified, demonstrating that the approach is highly effective and general. We expect that the wide applicability and simplicity of our approach will enable improving the robustness of many DBMSs.

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@inproceedings {258888,
author = {Manuel Rigger and Zhendong Su},
title = {Testing Database Engines via Pivoted Query Synthesis},
booktitle = {14th USENIX Symposium on Operating Systems Design and Implementation (OSDI 20)},
year = {2020},
isbn = {978-1-939133-19-9},
pages = {667--682},
url = {https://www.usenix.org/conference/osdi20/presentation/rigger},
publisher = {USENIX Association},
month = nov

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