Code smell detection is essential to improve software quality, enhancing software
maintainability, and decrease the risk of faults and failures in the software system. In this …

Context: An excessive number of code smells make a software system hard to evolve and
maintain. Machine learning methods, in addition to metric-based and heuristic-based …

Purpose: Code smells are residuals of technical debt induced by the developers. They
hinder evolution, adaptability and maintenance of the software. Meanwhile, they are very …

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 …

Detecting code smells and treating them with refactoring are trivial part of maintaining vast
and sophisticated software. There is an urgent need for automatic system to treat code …

Code smells can compromise software quality in the long term by inducing technical debt.
For this reason, many approaches aimed at identifying these design flaws have been …

Code smells violate software development principles that make the software more prone to
errors and changes. Researchers have developed code smell detectors using manual and …

Code smells may be introduced in software due to market rivalry, work pressure deadline,
improper functioning, skills or inexperience of software developers. Code smells indicate …

Code smells are characteristics of the software that indicates a code or design problem
which can make software hard to understand, evolve, and maintain. There are several code …

Context: Code smells are symptoms of wrong design decisions or coding shortcuts that may
increase defect rate and decrease maintainability. Research on code smells is accelerating …