On the Prevalence, Impact, and Evolution of SQL code smells in Data-Intensive Systems

Biruk Asmare Muse, Masud Rahman, Csaba Nagy, Anthony Cleve, Foutse Khomh, Giuliano Antoniol

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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.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE/ACM 17th International Conference on Mining Software Repositories, MSR 2020
PublisherACM Press
Pages327-338
Number of pages12
ISBN (Electronic)9781450379571
DOIs
Publication statusPublished - 29 Jun 2020

Publication series

NameProceedings - 2020 IEEE/ACM 17th International Conference on Mining Software Repositories, MSR 2020

Keywords

  • Code smells
  • SQL code smells
  • data-intensive systems
  • database access

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