一句话：首次系统性研究图数据库管理系统查询优化缺陷的根因、表现与修复策略，并构建测试工具发现20个独特缺陷。
图数据库管理系统（GDBMS）在数据驱动应用中日益普及，查询优化是提升查询性能的关键阶段，但其实现复杂且易引入缺陷。本文首次对GDBMS查询优化缺陷进行特征研究，从根因、表现形式和修复策略三个维度分析，提炼出10项新发现。基于该研究，作者设计并实现了一个面向GDBMS查询优化缺陷的测试工具。评估中工具共发现20个此前未知的GDBMS缺陷，其中10个属于查询优化缺陷，验证了工具的有效性并揭示了该类缺陷的普遍性与特殊性。
Recent years have witnessed an ever-growing usage of graph database management systems (GDBMSs) in various data-driven applications. Query optimization aims to improve the performance of database queries by identifying the most efficient way to execute them, and is an important stage of GDBMS workflow. Like other sophisticated systems, such as compilers, the query optimization process is complex and its implementation is prone to bugs. This paper conducts the first characteristic study of query optimization bugs in GDBMSs, including the root causes, manifestation methods, and fix strategies, and delivers 10 novel and important findings about them. Based on the characteristic study, we also developed a testing tool tailored to uncover GDBMS query optimization bugs, and the tool found 20 unique GDBMS bugs, 10 of which are query optimization bugs.