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An Empirical Study on the Characteristics of Database Access Bugs in Java Applications

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arxiv 2405.15008 v1 pith:KCXUS5QY submitted 2024-05-23 cs.SE cs.DB

classification cs.SEcs.DB
keywords databaseaccessbugsapplicationscausesqueriesrootcategories
verification ladder T0 review T1 audit T2 compute T3 formal
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Database-backed applications rely on the database access code to interact with the underlying database management systems (DBMSs). Although many prior studies aim at database access issues like SQL anti-patterns or SQL code smells, there is a lack of study of database access bugs during the maintenance of database-backed applications. In this paper, we empirically investigate 423 database access bugs collected from seven large-scale Java open source applications that use relational database management systems (e.g., MySQL or PostgreSQL). We study the characteristics (e.g., occurrence and root causes) of the bugs by manually examining the bug reports and commit histories. We find that the number of reported database and non-database access bugs share a similar trend but their modified files in bug fixing commits are different. Additionally, we generalize categories of the root causes of database access bugs, containing five main categories (SQL queries, Schema, API, Configuration, SQL query result) and 25 unique root causes. We find that the bugs pertaining to SQL queries, Schema, and API cover 84.2% of database access bugs across all studied applications. In particular, SQL queries bug (54%) and API bug (38.7%) are the most frequent issues when using JDBC and Hibernate, respectively. Finally, we provide a discussion on the implications of our findings for developers and researchers.

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  1. Toward Understanding Bugs in Vector Database Management Systems

    cs.SE 2025-06 conditional novelty 6.0 of 10

    A manual study of 1,463 confirmed bugs in 15 vector database systems yields a taxonomy of 5 symptom categories, 31 root causes, and 12 fix strategies.

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