Software quality is critical, as low quality, or “Code smell,” increases technical debt and
maintenance costs. There is a timely need for a collaborative model that detects and …

Code smell refers to substandard design patterns in software's source code that may lead to
faults-prone implementation. Machine learning-based code smell prediction models suffer …

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 …

(1) Background: Code smell is the most popular and reliable method for detecting potential
errors in code. In real-world circumstances, a single source code may have multiple code …

Featured Application ReMAHA–CatBoost is an advanced machine learning model designed
for predicting traffic accident severity. It is constructed in two parts: ReMAHA (relief–F-based …

Indian Sign Language (ISL) is a standardized and commonly used medium of
communication for the deaf and dumb community in India. Despite an enormous deaf and …

Detecting code smells using machine learning presents inherent challenges due to the
unbalanced nature of the problem and susceptibility to interpretation biases. The objective of …