Refactoring practices in the context of data-intensive systems
Developers often refactor code to improve the maintainability and comprehension of the software. There are many studies on refactoring activities in traditional software systems. However, refactoring in data-intensive systems is not well explored. Understanding the refactoring practices of developer...
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| Published in | Empirical software engineering : an international journal Vol. 28; no. 2; p. 46 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.03.2023
Springer Nature B.V |
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| Online Access | Get full text |
| ISSN | 1382-3256 1573-7616 |
| DOI | 10.1007/s10664-022-10271-x |
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| Abstract | Developers often refactor code to improve the maintainability and comprehension of the software. There are many studies on refactoring activities in traditional software systems. However, refactoring in data-intensive systems is not well explored. Understanding the refactoring practices of developers is important to develop efficient tool support. We conducted a longitudinal study of refactoring activities in data-access classes using 29 SQL and NoSQL database based data-intensive systems. We investigated the prevalence, co-occurrence, and evolution of data-access refactorings, and the association of data-access refactorings with data-access smells. We also conducted a manual analysis of 500 samples of data-access refactoring instances to identify the functionalities of the code that are targeted by such refactorings. Furthermore, we analyzed 500 sample data-access refactoring commits to understand the context behind the applied refactorings and explored the characteristics and contribution of developers involved in the refactorings. We also conducted a developer survey to complement our analysis on the subject systems. Our results show that data-access refactorings are prevalent and different in type. Most of the data-access refactorings target codes that implement data fetching and insertion, but they mostly do not modify data-access queries. Most of the data-access refactorings are done when adding or modifying features and during bug fixes. data-access refactoring is often performed by developers with higher development and refactoring experience. Overall, the results show that data-access refactorings focus on improving the code quality but not optimizing the underlying data-access operations by fixing data-access smells. Hence, more work is needed from the research community on providing awareness and support to practitioners on the benefits of addressing data-access smells with refactorings. |
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| AbstractList | Developers often refactor code to improve the maintainability and comprehension of the software. There are many studies on refactoring activities in traditional software systems. However, refactoring in data-intensive systems is not well explored. Understanding the refactoring practices of developers is important to develop efficient tool support. We conducted a longitudinal study of refactoring activities in data-access classes using 29 SQL and NoSQL database based data-intensive systems. We investigated the prevalence, co-occurrence, and evolution of data-access refactorings, and the association of data-access refactorings with data-access smells. We also conducted a manual analysis of 500 samples of data-access refactoring instances to identify the functionalities of the code that are targeted by such refactorings. Furthermore, we analyzed 500 sample data-access refactoring commits to understand the context behind the applied refactorings and explored the characteristics and contribution of developers involved in the refactorings. We also conducted a developer survey to complement our analysis on the subject systems. Our results show that data-access refactorings are prevalent and different in type. Most of the data-access refactorings target codes that implement data fetching and insertion, but they mostly do not modify data-access queries. Most of the data-access refactorings are done when adding or modifying features and during bug fixes. data-access refactoring is often performed by developers with higher development and refactoring experience. Overall, the results show that data-access refactorings focus on improving the code quality but not optimizing the underlying data-access operations by fixing data-access smells. Hence, more work is needed from the research community on providing awareness and support to practitioners on the benefits of addressing data-access smells with refactorings. |
| ArticleNumber | 46 |
| Author | Khomh, Foutse Muse, Biruk Asmare Antoniol, Giuliano |
| Author_xml | – sequence: 1 givenname: Biruk Asmare orcidid: 0000-0001-8861-9526 surname: Muse fullname: Muse, Biruk Asmare email: biruk-asmare.muse@polymtl.ca organization: Polytechnique Montréal – sequence: 2 givenname: Foutse surname: Khomh fullname: Khomh, Foutse organization: Polytechnique Montréal – sequence: 3 givenname: Giuliano surname: Antoniol fullname: Antoniol, Giuliano organization: Polytechnique Montréal |
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| Copyright | The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| Copyright_xml | – notice: The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Keywords | Data-access classes Data-intensive systems Database access Empirical study |
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