The accuracy reported for code smell-detecting tools varies depending on the dataset used
to evaluate the tools. Our survey of 45 existing datasets reveals that the adequacy of a …

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 …

Detecting code smells may be highly helpful for reducing maintenance costs and raising
source code quality. Code smells facilitate developers or researchers to understand several …

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

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 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 …

Software maintenance is an imperative step in software development. Code smells can arise
as a result of poor design as well as frequent code changes due to changing needs. Early …

Code smells detection primarily adopts heuristic-based, machine learning, and deep
learning approaches, However, to enhance accuracy, most studies employ deep learning …

Abstract Code Smell Detection (CSD) plays a crucial role in improving software quality and
maintainability. And Deep Learning (DL) techniques have emerged as a promising …

This paper aims to explore the application of deep learning in smart contract vulnerabilities
detection. Smart contracts are an essential part of blockchain technology and are crucial for …