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 …

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 …

Context Code smells are patterns in source code associated with an increased defect rate
and a higher maintenance effort than usual, but without a clear definition. Code smells are …

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 are poor code design or implementation that affect the code maintenance
process and reduce the software quality. Therefore, code smell detection is important in …

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

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

Context: Software design problems emerge when internal structures of source code
challenge design principles or rules. The prediction of design problems plays an essential …

Due to rapid development in the software industry, various software is being developed,
which compromises the software quality. As long as time passes, the software which …

Code smells are structures in code that imply potential maintainability problems and may
negatively impact software quality. One of the critical challenges with code smells is that …