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Junhao Lan

dblp:386/5414 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0008-1299-7502ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Software testing · 100%
Databases, data mining, and information retrieval
1 paper
Graph data management · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Graph data management
graph database
0.812024
Testing Graph Database Systems with Graph-State Persistence Oracle · ISSTA 2024
Software testing › database testing
graph database testing
0.812024
Testing Graph Database Systems with Graph-State Persistence Oracle · ISSTA 2024
Software testing
metamorphic testing
0.812024
Testing Graph Database Systems with Graph-State Persistence Oracle · ISSTA 2024
Software testing › test oracle
metamorphic test oracle
0.812024
Testing Graph Database Systems with Graph-State Persistence Oracle · ISSTA 2024
Software testing
test oracle
0.812024
Testing Graph Database Systems with Graph-State Persistence Oracle · ISSTA 2024

Methods — techniques the papers use, named apart from their topics

mutation rules · 1.5labeled property graph isomorphism · 1.5
YearPublicationVenuePosition
2024 Testing Graph Database Systems with Graph-State Persistence Oracle
abstract
Graph Database Management Systems (GDBMSs) store data in a graph format, facilitating rapid querying of nodes and relationships. This structure is particularly advantageous for applications like social networks and recommendation systems, which often involve frequent writing operations—such as adding new nodes, creating relationships, or modifying existing data—that potentially introduce bugs. However, existing GDBMS testing approaches tend to overlook these writing functionalities, failing to detect bugs arising from such operations. In this paper we present GraspDB, the first metamorphic testing approach specifically designed to identify bugs related to writing operations in graph database systems. GraspDB employs the Graph-State Persistence oracle, which is based on the Labeled Property Graph Isomorphism (LPG-Isomorphism) and Labeled Property Subgraph Isomorphism (LPSG-Isomorphism) relations. We also develop three classes of mutation rules aimed at engaging more diverse writing-related code logic. GraspDB has successfully detected 77 unique, previously unknown bugs across four popular open source graph database engines, among which 58 bugs are confirmed by developers, 43 bugs have been fixed and 31 are related to writing operations.
Shuang Liu 0007, Junhao Lan, Xiaoning Du 0001, Jiyuan Li, Wei Lu 0015, Jiajun Jiang, Xiaoyong Du 0001
ISSTA2