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 …

In recent years, many studies on detecting code smells in source code have published
datasets with limited characteristics, such as the ambiguity of code smell definitions leads to …

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 …

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 …

Python is an increasingly popular programming language used in various software projects
and domains. Code smells in Python significantly influences the maintainability …

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 …

Background: Code smells are symptoms that something may be wrong in software systems
that can cause complications in maintaining software quality. In literature, there exist many …

Context: An excessive number of code smells make a software system hard to evolve and
maintain. Machine learning methods, in addition to metric-based and heuristic-based …

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 …

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