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Python code smells detection using conventional machine learning models [PDF]

open access: yesPeerJ Computer Science, 2023
Code smells are poor code design or implementation that affect the code maintenance process and reduce the software quality. Therefore, code smell detection is important in software building.
Rana Sandouka, Hamoud Aljamaan
doaj   +4 more sources

Empirical study of the relationship between design patterns and code smells. [PDF]

open access: goldPLoS ONE, 2020
Software systems are often developed in such a way that good practices in the object-oriented paradigm are not met, causing the occurrence of specific disharmonies which are sometimes called code smells.
Mahmoud Alfadel   +2 more
doaj   +4 more sources

An Empirical Investigation on the Effect of Code Smells on Resource Usage of Android Mobile Applications [PDF]

open access: goldIEEE Access, 2021
Code smells refer to suboptimal coding practices which impact software quality and software non-functional requirements such as performance, maintainability, and resource usage.
Mohammad A. Alkandari   +2 more
doaj   +3 more sources

A Severity Assessment of Python Code Smells

open access: yesIEEE Access, 2023
Presence of code smells complicate the source code and can obstruct the development and functionality of the software project. As they represent improper behavior that might have an adverse effect on software maintenance, code smells are behavioral in ...
Aakanshi Gupta   +5 more
doaj   +3 more sources

Dynamic stacking ensemble for cross-language code smell detection [PDF]

open access: goldPeerJ Computer Science
Code smells refer to poor design and implementation choices by software engineers that might affect the overall software quality. Code smells detection using machine learning models has become a popular area to build effective models that are capable of ...
Hamoud Aljamaan
doaj   +4 more sources

Code Smells for Machine Learning Applications [PDF]

open access: yesProceedings of the 1st International Conference on AI Engineering: Software Engineering for AI, 2022
The popularity of machine learning has wildly expanded in recent years. Machine learning techniques have been heatedly studied in academia and applied in the industry to create business value.
Haiyin Zhang, Luís Cruz, A. Deursen
semanticscholar   +4 more sources

An Analytical Study of Code Smells

open access: yesTehnički Glasnik, 2021
Software development process involves developing, building and enhancing high-quality software for specific tasks and as a consequence generates considerable amount of data.
Lida Bamizadeh   +3 more
doaj   +3 more sources

A systematic literature review: Refactoring for disclosing code smells in object oriented software

open access: goldAin Shams Engineering Journal, 2018
Context: Reusing a design pattern is not always in the favor of developers. Thus, the code starts smelling. The presence of “Code Smells” leads to more difficulties for the developers.
Satwinder Singh, Sharanpreet Kaur
doaj   +2 more sources

Are architectural smells independent from code smells? An empirical study [PDF]

open access: greenJournal of Systems and Software, 2019
(in press)
Francesca Arcelli Fontana   +3 more
openalex   +7 more sources

A study of dealing class imbalance problem with machine learning methods for code smell severity detection using PCA-based feature selection technique [PDF]

open access: yesScientific Reports, 2023
Detecting code smells may be highly helpful for reducing maintenance costs and raising source code quality. Code smells facilitate developers or researchers to understand several types of design flaws. Code smells with high severity can cause significant
Rajwant Singh Rao   +3 more
doaj   +2 more sources

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