Testing Graph Database Engines via Query Partitioning
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Author / Producer
Date
2023-07
Publication Type
Conference Paper
ETH Bibliography
yes
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Abstract
Graph Database Management Systems (GDBMSs) store data as graphs and allow the efficient querying of nodes and their relationships. Logic bugs are bugs that cause a GDBMS to return an incorrect result for a given query (e.g., by returning incorrect nodes or relationships). The impact of such bugs can be severe, as they often go unnoticed. The core insight of this paper is that Query Partitioning, a test oracle that has been proposed to test Relational Database Systems, is applicable to testing GDBMSs as well. The core idea of Query Partitioning is that, given a query, multiple queries are derived whose results can be combined to reconstruct the given query's result. Any discrepancy in the result indicates a logic bug. We have implemented this approach as a practical tool named GDBMeter and evaluated GDBMeter on three popular GDBMSs and found a total of 40 unique, previously unknown bugs. We consider 14 of them to be logic bugs, the others being error or crash bugs. Overall, 27 of the bugs have been fixed, and 35 confirmed. We compared our approach to the state-of-the-art approach to testing GDBMS, which relies on differential testing; we found that it results in a high number of false alarms, while Query Partitioning reported actual logic bugs without any false alarms. Furthermore, despite the previous efforts in testing Neo4j and JanusGraph, we found 18 additional bugs. The developers appreciate our work and plan to integrate GDBMeter into their testing process. We expect that this simple, yet effective approach and the practical tool will be used to test other GDBMSs.
Permanent link
Publication status
published
External links
Book title
ISSTA 2023: Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis
Journal / series
Volume
Pages / Article No.
140 - 149
Publisher
Association for Computing Machinery
Event
32nd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2023)
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Database testing; Graph databases; Test oracle; Automatic testing
Organisational unit
09628 - Su, Zhendong / Su, Zhendong