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

Author:

Liu Wei1ORCID,Mondal Shouvick2ORCID,Chen Tse-Hsun (Peter)1ORCID

Affiliation:

1. Software PErformance, Analysis, and Reliability (SPEAR) lab, Concordia University, Canada

2. Software Engineering and Testing (SET) lab, Indian Institute of Technology Gandhinagar, India

Abstract

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.

Publisher

Association for Computing Machinery (ACM)

Reference75 articles.

1. [n. d.]. channable/dbcritic. https://github.com/channable/dbcritic. (Accessed on 03/25/2023).

2. [n. d.]. DB OPTIMIZATION SERVICE - Holistic.dev. https://holistic.dev/. (Accessed on 03/25/2023).

3. 2009. What Java ORM do you prefer and why? https://stackoverflow.com/questions/452385/what-java-orm-do-you-prefer-and-why

4. 2012. JPA or JDBC how are they different? https://stackoverflow.com/questions/11881548/jpa-or-jdbc-how-are-they-different/

5. 2021. Replication Package. https://github.com/SPEAR-SE/empirical-db-issue-data

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3