A multivocal mapping study of mongoDB smells
- Cherry, Boris Namur Digital Institute, University of Namur, Belgium
- Bernard, Jehan Namur Digital Institute, University of Namur, Belgium
- Kintziger, Thomas Namur Digital Institute, University of Namur, Belgium
- Nagy, Csaba ORCID Istituto del software (SI), Facoltà di scienze informatiche, Università della Svizzera italiana, Svizzera
- Cleve, Anthony Namur Digital Institute, University of Namur, Belgium
- Lanza, Michele ORCID Istituto del software (SI), Facoltà di scienze informatiche, Università della Svizzera italiana, Svizzera
- 2024
Published in:
- 2024 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER). - 2024, p. 792-803
English
Code smells are symptoms of poor design or bad implementation choices. Their automatic detection is helpful for various reasons. For example, the detected smells can guide developers during code inspection to find the causes of maintenance problems. Many code smells have been proposed for several technologies, including database communication, such as ORM or SQL antipatterns. However, despite its popularity, no research has been conducted on MongoDB smells. We present a systematic multivocal literature mapping study, also covering “grey” literature, to build a catalog of MongoDB code smells. After evaluating 1,498 artifacts (e.g., blog posts, online articles, book chapters, scientific papers, presentation slides, and videos) from 12 search engines, we manually reviewed 174 sources and devised a catalog of 76 smells organized into 11 categories. We present the catalog of MongoDB code smells through a series of examples.
- Collections
- Language
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- English
- Classification
- Computer science and technology
- License
- License undefined
- Open access status
- green
- Identifiers
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- DOI 10.1109/SANER60148.2024.00086
- ARK ark:/12658/srd1329705
- Persistent URL
- https://n2t.net/ark:/12658/srd1329705
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