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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 et Giuliano Antoniol

Communication écrite (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.

Mots clés

code smells; database access, SQL code smells; data-intensive systems

Sujet(s): 2700 Technologie de l'information > 2705 Logiciels et développement
2700 Technologie de l'information > 2706 Génie logiciel
Département: Département de génie informatique et génie logiciel
URL de PolyPublie: https://publications.polymtl.ca/9344/
Nom de la conférence: 17th International Conference on Mining Software Repositories (MSR 2020)
Lieu de la conférence: Seoul, Republic of Korea
Date(s) de la conférence: 2020-06-29 - 2020-06-30
Maison d'édition: ACM
DOI: 10.1145/3379597.3387467
URL officielle: https://doi.org/10.1145/3379597.3387467
Date du dépôt: 06 sept. 2023 13:20
Dernière modification: 25 sept. 2024 15:45
Citer en APA 7: Muse, B. A., Rahman, M. M., Nagy, C., Cleve, A., Khomh, F., & Antoniol, G. (juin 2020). On the prevalence, impact and evolution of SQL Code smells in data-intensive systems [Communication écrite]. 17th International Conference on Mining Software Repositories (MSR 2020), Seoul, Republic of Korea. https://doi.org/10.1145/3379597.3387467

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