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 …

Graph database engines stand out in the era of big data for their efficiency of modeling and
processing linked data. To assure high quality of graph database engines, it is highly critical …

Database Management Systems (DBMSs) provide efficient data retrieval and manipulation
for many applications through Structured Query Language (SQL). Incorrect implementations …

Transactions are used to maintain the data integrity of databases, and have become an
indispensable feature in modern Database Management Systems (DBMSs). Despite …

Database Management Systems (DBMSs) utilize transactions to ensure the consistency and
integrity of data. Incorrect transaction implementations in DBMSs can lead to severe …

Graph database systems (GDBs) allow efficiently creating, modifying, and retrieving graph
data in a graph database. To accelerate graph queries, GDBs usually adopt various and …

Differential testing is a prevalent strategy for establishing test oracles in automated DBMS
testing. However, meticulously selecting equivalent DBMSs with diverse implementations …

Deep learning (DL) is a critical tool for real-world applications, and comprehensive testing of
DL models is vital to ensure their quality before deployment. However, recent studies have …

Graph Database Systems (GDBs) support efficiently storing and retrieving graph data, and
have become a critical component in many important applications. Many widely-used GDBs …

Graph Database Management Systems (GDBMSs) store graphs as data. They are used
naturally in applications such as social networks, recommendation systems and program …