Detecting Logic Bugs in Graph Database Management Systems via Injective and Surjective Graph Query Transformation

Jiang, Yuancheng; Liu, Jiahao; Ba, Jinsheng; Yap, Roland H. C.; Liang, Zhenkai; Rigger, Manuel

doi:10.1145/3597503.3623307

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2024

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Cited by 2 publications

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Mutation-Based Integration Testing of Knowledge Graph Applications

John,

Johnsen,

Kamburjan

2024

2024 IEEE 35th International Symposium on Software Reliability Engineering (ISSRE)

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Mutation-Based Integration Testing of Knowledge Graph Applications

John,

Johnsen,

Kamburjan

2024

2024 IEEE 35th International Symposium on Software Reliability Engineering (ISSRE)

View full text Add to dashboard Cite

Keep It Simple: Testing Databases via Differential Query Plans

Ba,

Rigger

2024

Proc. ACM Manag. Data

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Query optimizers perform various optimizations, many of which have been proposed to optimize joins. It is pivotal that these optimizations are correct, meaning that they should be extensively tested. Besides manually written tests, automated testing approaches have gained broad adoption. Such approaches semi-randomly generate databases and queries. More importantly, they provide a so-called test oracle that can deduce whether the system's result is correct. Recently, researchers have proposed a novel testing approach called Transformed Query Synthesis (TQS) specifically designed to find logic bugs in join optimizations. TQS is a sophisticated approach that splits a given input table into several sub-tables and validates the results of the queries that join these sub-tables by retrieving the given table. We studied TQS's bug reports, and found that 14 of 15 unique bugs were reported by showing discrepancies in executing the same query with different query plans. Therefore, in this work, we propose a simple alternative approach to TQS. Our approach enforces different query plans for the same query and validates that the results are consistent. We refer to this approach as Differential Query Plan (DQP) testing. DQP can reproduce 14 of the 15 unique bugs found by TQS, and found 26 previously unknown and unique bugs. These results demonstrate that a simple approach with limited novelty can be as effective as a complex, conceptually appealing approach. Additionally, DQP is complementary to other testing approaches for finding logic bugs. 81% of the logic bugs found by DQP cannot be found by NoREC and TLP, whereas DQP overlooked 86% of the bugs found by NoREC and TLP. We hope that the practicality of our approach---we implemented in less than 100 lines of code per system---will lead to its wide adoption.

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Detecting Logic Bugs in Graph Database Management Systems via Injective and Surjective Graph Query Transformation

Cited by 2 publications

References 25 publications

Mutation-Based Integration Testing of Knowledge Graph Applications

Mutation-Based Integration Testing of Knowledge Graph Applications

Keep It Simple: Testing Databases via Differential Query Plans

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