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 …

Due to the proliferation of large language models (LLMs) and their widespread use in
applications such as ChatGPT, there has been a significant increase in interest in AI over the …

Code smells indicate design issues that violate basic design principles such as hierarchy
encapsulation, abstraction, and others, potentially affecting software quality [1],[2]. Detecting …

Code smell detection can be very useful for minimizing maintenance costs and improving
software quality. Code smells help developers/programmers, researchers to subjectively …

Code smells combine software features that indicate a code or design-related problem that
can increase the difficulty of the software and make it complicated to recognize, develop …

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

Code smells refers to any symptoms or anomalies in the source code that shows violation of
design principles or implementation. Early detection of bad code smells improves software …

Code smell is a software characteristic that indicates bad symptoms in code design which
causes problems related to software quality. The severity of code smells must be measured …

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 Smell is a set of information of a source code that indicates any serious problem in the
software. To detect the code smell prediction rule, we have applied a Decision tree …