Code smells are poor design and implementation choices that hinders the overall software
quality. Code smells detection using machine learning models has been an active research …

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 …

Unlike code errors, the presence of code smell often does not affect the behavior of the
software system, but it will cause quality problems in terms of readability, understandability …

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

Several approaches are proposed to detect code smells. A set of important approaches are
based on machine learning algorithms, which require the code smells have been labeled in …

We conducted a systematic literature review of the most recent studies to survey the existing
ML-based methods for code smell detection. A systematic search of well-established digital …

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 indicate potential symptoms or problems in software due to inefficient design or
incomplete implementation. These problems can affect software quality in the long-term …

Code smells is the term used to signal certain patterns or structures in software code that
may contain a potential design or architecture problem, leading to maintainability or other …