Examining deep learning's capability to spot code smells: a systematic literature review

R Malhotra, B Jain, M Kessentini - Cluster Computing, 2023 - Springer
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 smell detection based on supervised learning models: A survey

Y Zhang, C Ge, H Liu, K Zheng - Neurocomputing, 2024 - Elsevier
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 …

Data preparation for deep learning based code smell detection: A systematic literature review

F Zhang, Z Zhang, JW Keung, X Tang, Z Yang… - Journal of Systems and …, 2024 - Elsevier
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 …

A systematic review of refactoring opportunities by software antipattern detection

S Kalhor, MR Keyvanpour, A Salajegheh - Automated Software …, 2024 - Springer
The violation of the semantic and structural software principles, such as low connection, high
coherence, high understanding, and others, are called anti-patterns, which is one of the …

Application of Deep Learning for Code Smell Detection: Challenges and Opportunities

M Hadj-Kacem, N Bouassida - SN Computer Science, 2024 - Springer
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 …

SADSE: Search-based Anti-pattern Detection Method by Standard Examples

S Kalhor, A Salajegheh, A Broumandnia - 2023 - researchsquare.com
Anti-patterns occur when software design principles are not followed in the software design
and coding process. Although there may be no errors or bugs in the software …