一句话：提出面向基于 Gremlin 的图数据库系统的随机差分测试方法，自动发现导致查询结果错误的逻辑缺陷。
图数据库系统在知识图谱、社交网络和欺诈检测等应用中至关重要，但其逻辑错误——即给定查询返回错误结果——却比关系数据库系统受到更少关注。本文提出一种随机差分测试方法，针对基于 Gremlin 的图数据库系统进行缺陷检测：随机生成图数据与 Gremlin 查询，在多个图数据库系统上执行并比较查询结果，将结果不一致视为潜在逻辑错误。该方法旨在缓解复杂图与查询下错误易被忽视的问题，并已在基于 Gremlin 的图数据库系统中用于发现逻辑缺陷，表明随机差分测试对图数据库正确性保障具有实用价值。
Graph database systems (GDBs) allow efficiently storing and retrieving graph data, and have become the critical component in many applications, e.g., knowledge graphs, social networks, and fraud detection. It is important to ensure that GDBs operate correctly. Logic bugs can occur and make GDBs return an incorrect result for a given query. These bugs are critical and can easily go unnoticed by developers when the graph and queries become complicated. Despite the importance of GDBs, logic bugs in GDBs have received less attention than those in relational database systems.
DOI 原文 ·
@inproceedings{paperbot7440,
title = {Finding bugs in Gremlin-based graph database systems via Randomized differential testing},
author = {Yingying Zheng and Wensheng Dou and Yicheng Wang and Zheng Qin and Lei Tang and Yu Gao and Dong Wang and Wei Wang and Jun Wei},
booktitle = {ISSTA},
year = {2022},
doi = {10.1145/3533767.3534409}
}