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On the prevalence, impact and evolution of SQL Code smells in data-intensive systems

Biruk Asmare Muse, Mohammad Masudur Rahman, Csaba Nagy, Anthony Cleve, Foutse Khomh and Giuliano Antoniol

Paper (2020)

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Abstract

Code smells indicate software design problems that harm software quality. Data-intensive systems that frequently access databases often suffer from SQL code smells besides the traditional smells. While there have been extensive studies on traditional code smells, recently, there has been a growing interest in SQL code smells. In this paper, we conduct an empirical study to investigate the prevalence and evolution of SQL code smells in open-source, data-intensive systems. We collected 150 projects and examined both traditional and SQL code smells in these projects. Our investigation delivers several important findings. First, SQL code smells are indeed prevalent in data-intensive software systems. Second, SQL code smells have a weak co-occurrence with traditional code smells. Third, SQL code smells have a weaker association with bugs than that of traditional code smells. Fourth, SQL code smells are more likely to be introduced at the beginning of the project lifetime and likely to be left in the code without a fix, compared to traditional code smells. Overall, our results show that SQL code smells are indeed prevalent and persistent in the studied data-intensive software systems. Developers should be aware of these smells and consider detecting and refactoring SQL code smells and traditional code smells separately, using dedicated tools.

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Subjects: 2700 Information technology > 2705 Software and development
2700 Information technology > 2706 Software engineering
Department: Department of Computer Engineering and Software Engineering
ISBN: 9781450375177
PolyPublie URL: https://publications.polymtl.ca/9344/
Conference Title: 17th International Conference on Mining Software Repositories (MSR 2020)
Conference Location: Seoul, Republic of Korea
Conference Date(s): 2020-06-29 - 2020-06-30
Publisher: ACM
DOI: 10.1145/3379597.3387467
Official URL: https://doi.org/10.1145/3379597.3387467
Date Deposited: 06 Sep 2023 13:20
Last Modified: 25 Sep 2024 15:45
Cite in APA 7: Muse, B. A., Rahman, M. M., Nagy, C., Cleve, A., Khomh, F., & Antoniol, G. (2020, June). On the prevalence, impact and evolution of SQL Code smells in data-intensive systems [Paper]. 17th International Conference on Mining Software Repositories (MSR 2020), Seoul, Republic of Korea. https://doi.org/10.1145/3379597.3387467

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