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 detection helps in improving understandability and maintainability of software
while reducing the chances of system failure. In this study, six machine learning algorithms …

Code smell detection is critical for calculating system quality and identifying issues that
require more work and development. The technique of finding wrongly developed code …

Code smells are symptoms of poor software design and implementation choices. Previous
empirical studies have underlined their negative effect on software comprehension, fault …

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 …

The presence of code smells will increase the risk of failure, make software difficult to
maintain, and introduce potential technique debt in the future. Although many deep-learning …

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 the result of not following software engineering principles during software
development, especially in the design and coding phase. It leads to low maintainability. To …

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 are indicators of deeper problems in source code that affect the system
maintainability and evolution. Detecting code smells is crucial as a software maintenance …