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 …

Artificial intelligence (AI) has witnessed an exponential increase in use in various
applications. Recently, the academic community started to research and inject new AI-based …

Abstract Code Smell Severity Prioritization (CSSP) is crucial in helping software developers
minimize software maintenance costs and enhance software quality, particularly when faced …

Code smell refers to substandard design patterns in software's source code that may lead to
faults-prone implementation. Machine learning-based code smell prediction models suffer …

Code smell identification is crucial in software maintenance. The existing literature mostly
focuses on single code smell identification. However, in practice, a software artefact typically …

(1) Background: Code smell is the most popular and reliable method for detecting potential
errors in code. In real-world circumstances, a single source code may have multiple code …

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 …

Ohjelmat ovat nykypäivänä aiempaa laajempia koodimäärässä mitattuna, ja tekniikoiden ja
työkalujen kehityksen ansiosta koodin tuottamisen tehokkuus on myös kasvanut. Ohjelmien …