To preserve software quality and maintainability, machine learning-based code smell
detection has been proposed, and the results are promising. This research proposes an …

Code smells are the result of not following software engineering principles during software
development, especially in the design and coding phase. It leads to low maintainability. To …

Code smells detection helps in improving understandability and maintainability of software
while reducing the chances of system failure. In this study, six machine learning algorithms …

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 …

Context: Code smell detection is the process of identifying code pieces that are poorly
designed and implemented. Recently more research has been directed towards machine …

Code smells are structures in the source code that suggest the possibility of refactorings.
Consequently, developers may identify refactoring opportunities by detecting code smells …

Code smells frequently leads to the discovery of decreased code quality, drains on
application resources, or even critical security vulnerabilities embedded within the …

We examine a machine learning approach for detecting common Class and Method level
code smells (Data Class and God Class, Feature Envy and Long Method). The focus of the …

Supervised learning-based code smell detection has become one of the dominant
approaches to identify code smell. Existing works optimize the process of code smell …

Code smells are indicators of potential problems in software. They tend to have a negative
impact on software quality. Several studies use machine learning techniques to detect bad …