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 …

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 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 …

Code smells are structures in code that may indicate maintainability issues. They are
challenging to define, and software engineers detect them differently. Mitigation of this …

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 …

This literature review surveys the extant research from 2018 through October 2022 in three
key conferences related to software engineering and repository mining: Mining Software …

As one of the most common code smells, feature envy reduces the cohesion of classes and
increases the coupling between classes, thus leading to difficulty of software maintainability …

Researchers apply machine-learning techniques for code smell detection to counter the
subjectivity of many code smells. Such approaches need a large, manually annotated …

Software testing plays a critical role in the development and the assurance of the software
quality. However, the quality of the code that is responsible for testing may, itself, be affected …

Context: As a typical code smell, feature envy occurs when a method exhibits excessive
reliance and usage on specific functionalities of another class, which can lead to issues with …