Machine learning‐based code smell detection (CSD) has been demonstrated to be a
valuable approach for improving software quality and enabling developers to identify …

Software energy efficiency is an increasingly relevant aspect that should be taken into
account during software development and some of the most common design and coding …

Poor software design introduced anti-patterns in the design phase. It reduces the rate of
maintainability and re-usability of the software. To investigate anti-patterns in the early stage …

A code smell is one of the main reasons for generating low-quality software. To make the
software scalable, manageable, and reusable code smell detection is required. In this work …

Abstract Design patterns are used to address common design problems in software systems.
Several machine learning models have been proposed for detecting and recommending …

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 …

Code smells are indicators of code anomalies in poorly implemented or designed software
programs. In addition to code fault-proneness and software defects, code smells may …