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 …

The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …

Code smell is the structural design defect that makes programs difficult to understand,
maintain, and evolve. Existing works of code smell detection mainly focus on prevalent code …

The violation of the semantic and structural software principles, such as low connection, high
coherence, high understanding, and others, are called anti-patterns, which is one of the …

Code smells are early warning signs of potential issues in software quality. Various
techniques are used in code smell detection, including the Bayesian approach, rule-based …

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 …

Efficiently identifying and resolving code smells enhances software project quality. This
paper presents a novel solution, utilizing automated machine learning (AutoML) techniques …

In the era of Industry 4.0 and 5.0, a transformative wave of softwarisation has surged. This
shift towards software-centric frameworks has been a cornerstone and has highlighted the …

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 …