An empirical study on configuration-related branch statement in database management system

Xie Li; Huiping Zhou; Haifang Zhou; Jingying Zhang

doi:10.1117/12.3006402

26 September 2023 An empirical study on configuration-related branch statement in database management system

Xie Li, Huiping Zhou, Haifang Zhou, Jingying Zhang

Proceedings Volume 12793, International Conference on Mechatronics and Intelligent Control (ICMIC 2023); 127930D (2023) https://doi.org/10.1117/12.3006402
Event: International Conference on Mechatronics and Intelligent Control (ICMIC2023), 2023, Wuhan, China

Abstract

Database management systems introduce thousands of configuration options to provide flexibility. However, configuration complexity and configuration dependencies have inevitably affect the system reliability and become one of the major causes of system failure. Previous research neither specifically detects configuration-related bugs nor studies the characteristics of configuration-related code in DBMSs. In this paper, we undertake one of the first attempts to conduct a real-world configuration-related branch statements characteristic study in DBMSs. We first use a taint analysis tool to construct a data set of 347 real world configuration-related branch statements including 100 in MySQL, 98 in SQLite and 149 in PostgreSQL, which are very popular. Based on our study, we have obtained some findings: (1) More than half (53. 6%) of configuration-related branch statements contain only configuration variables, 93. 5% of which contain only one configuration variable. (2) 46. 4% of configuration-related branch statements contain not only configuration variables but also program variables. (3) Complex configuration-related branch statements (which contain function call) account for 17. 9%.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xie Li, Huiping Zhou, Haifang Zhou, and Jingying Zhang "An empirical study on configuration-related branch statement in database management system", Proc. SPIE 12793, International Conference on Mechatronics and Intelligent Control (ICMIC 2023), 127930D (26 September 2023); https://doi.org/10.1117/12.3006402

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