  Database Management System (DBMS) fuzzing is an automated testing technique
aimed at detecting errors and vulnerabilities in DBMSs by generating, mutating,
and executing test cases. It not only reduces the time and cost of manual
testing but also enhances detection coverage, providing valuable assistance in
developing commercial DBMSs. Existing fuzzing surveys mainly focus on
general-purpose software. However, DBMSs are different from them in terms of
internal structure, input/output, and test objectives, requiring specialized
fuzzing strategies. Therefore, this paper focuses on DBMS fuzzing and provides
a comprehensive review and comparison of the methods in this field. We first
introduce the fundamental concepts. Then, we systematically define a general
fuzzing procedure and decompose and categorize existing methods. Furthermore,
we classify existing methods from the testing objective perspective, covering
various components in DBMSs. For representative works, more detailed
descriptions are provided to analyze their strengths and limitations. To
objectively evaluate the performance of each method, we present an open-source
DBMS fuzzing toolkit, OpenDBFuzz. Based on this toolkit, we conduct a detailed
experimental comparative analysis of existing methods and finally discuss
future research directions.
