Search Results - Python code smell detection

Enhancing Python Code Smell Detection with Heterogeneous Ensembles

Authors: Rana Sandouka Hamoud Aljamaan

Source: International Journal of Software Engineering and Knowledge Engineering. 35:963-986

An Empirical Evaluation of Ensemble Models for Python Code Smell Detection

Authors: Rajwant Singh Rao Seema Dewangan Alok Mishra

Source: Applied Sciences, Vol 15, Iss 13, p 7472 (2025)

Subject Terms: Technology, QH301-705.5, Physics, QC1-999, Python code smell detection, ensemble learning models, Engineering (General). Civil engineering (General), SMOTE class balancing method, Chemistry, TA1-2040, Biology (General), chi-square feature selection technique, QD1-999

Access URL: https://doaj.org/article/d5355a98e88646b997415dd704137668

Enhancing Software Quality: Python Code Smell Detection using Machine Learning techniques and Refactoring Long Methods using Extract Method Algorithm

Authors: Mohammed Sharraf Uddin Kazi Zunayed Quader Knobo Jannatul Ferdoshi et al.

Source: Proceedings of the 2024 10th International Conference on Robotics and Artificial Intelligence. :93-102

Python code smells detection using conventional machine learning models

Authors: Rana Sandouka Hamoud Aljamaan

Source: PeerJ Computer Science, Vol 9, p e1370 (2023)

Subject Terms: Python, Code smell, Detection, Machine learning, Large class, Long method, Electronic computers. Computer science, QA75.5-76.95

File Description: electronic resource

Relation: https://peerj.com/articles/cs-1370.pdf; https://peerj.com/articles/cs-1370/; https://doaj.org/toc/2376-5992

Access URL: https://doaj.org/article/918c787e9a4d407ba38fafaca4018ddb

Python Code Smell Detection Using Machine Learning

Authors: Natthida Vatanapakorn Chitsutha Soomlek Pusadee Seresangtakul

Source: 2022 26th International Computer Science and Engineering Conference (ICSEC). :128-133

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Pioneering agentic retrieval-augmented generation in software quality: a novel framework for code smell detection via dynamic retrieval

Authors: Bushra Aljohani Abdulmajeed Aljuhani

Source: PeerJ Computer Science, Vol 12, p e3642 (2026)

Subject Terms: Retrieval-Augmented Generation (RAG), Agentic RAG, Code smell detection, Software quality, Large language models (LLMs), Electronic computers. Computer science, QA75.5-76.95

File Description: electronic resource

Relation: https://peerj.com/articles/cs-3642.pdf; https://peerj.com/articles/cs-3642/; https://doaj.org/toc/2376-5992

Access URL: https://doaj.org/article/73cf6d2f08394964b4f0977bd70fe065

PyExamine A Comprehensive, UnOpinionated Smell Detection Tool for Python

Authors: Shivashankar, Karthik Martini, Antonio

Index Terms: Computer Science - Software Engineering, text

URL: http://arxiv.org/abs/2501.18327

Cross-Language Code Smell Detection via Transfer Learning

Authors: Rana Sandouka Hamoud Aljamaan

Source: Applied Sciences, Vol 15, Iss 17, p 9293 (2025)

Subject Terms: transfer learning, machine learning, code smell, detection, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999

File Description: electronic resource

Relation: https://www.mdpi.com/2076-3417/15/17/9293; https://doaj.org/toc/2076-3417

Access URL: https://doaj.org/article/c43f55a44efa4c04a9be1e88ff6564ac

Optimizing Pre-Trained Code Embeddings With Triplet Loss for Code Smell Detection

Authors: Ali Nizam Ertugrul Islamoglu Omer Kerem Adali et al.

Source: IEEE Access, Vol 13, Pp 31335-31350 (2025)

Subject Terms: Code embedding, contrastive learning, triplet loss, code smell detection, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

File Description: electronic resource

Relation: https://ieeexplore.ieee.org/document/10890964/; https://doaj.org/toc/2169-3536

Access URL: https://doaj.org/article/9fe6b8a447d3493090bfb60feea8039c

Dynamic stacking ensemble for cross-language code smell detection.

Authors: Aljamaan, Hamoud

Source: PeerJ Computer Science; Aug2024, p1-29, 29p

Subject Terms: MACHINE learning, COMPUTER software quality control, PROGRAMMING languages, SOFTWARE engineers, STACKING machines, PYTHON programming language

Exploring the Efficacy of of GPT-3.5 in Code Smell Detection

Authors: Ahmed, Iftekhar LIU, YANG

Index Terms: Computer science, publication

URL: https://escholarship.org/uc/item/7339g3fg
https://escholarship.org/content/qt7339g3fg/qt7339g3fg.pdf

Detecting Inline Code Comment Smells Leveraging CodeBERT Model

Authors: Sajjad Mahmood

Source: IEEE Access, Vol 14, Pp 28367-28382 (2026)

Subject Terms: Inline code comments, comment smells, automated detection, CodeBERT embeddings, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

File Description: electronic resource

Relation: https://ieeexplore.ieee.org/document/11400723/; https://doaj.org/toc/2169-3536

Access URL: https://doaj.org/article/39b4d6838ea2435bac1ab2a54ebaf1bc

Metric-based code smell detection technique for python software

Authors: Leeman, Samaila Ja'afaru

Index Terms: Software maintenance, Python (Computer program language), Thesis, NonPeerReviewed

URL: http://psasir.upm.edu.my/id/eprint/90722/1/FSKTM%202019%2055%20IR.pdf
http://psasir.upm.edu.my/id/eprint/90722/
http://psasir.upm.edu.my/id/eprint/90722

A systematic review on software code smells.

Authors: Al-Obeidallah, Mohammed Ghazi Al-Fraihat, Dimah

Source: International Journal of Electrical & Computer Engineering (2088-8708); Jun2025, Vol. 15 Issue 3, p3010-3027, 18p

Subject Terms: PROGRAMMING languages, RELIABILITY in engineering, MACHINE learning, SYSTEMS software, SMELL

Python Code Smell Refactoring Route Generation Based on Association Rule and Correlation.

Authors: Wang, Guanglei Chen, Junhua Gao, Jianhua et al.

Source: International Journal of Software Engineering & Knowledge Engineering; Sep2021, Vol. 31 Issue 9, p1329-1347, 19p

Subject Terms: PYTHON programming language, COMPUTER software quality control, SOFTWARE architecture, SMELL, RANK correlation (Statistics), DESIGN software

Exploring the Efficacy of of GPT-3.5 in Code Smell Detection

Authors: LIU, YANG

Subject Terms: Computer science

File Description: application/pdf

Access URL: https://escholarship.org/uc/item/7339g3fg
https://escholarship.org/content/qt7339g3fg/qt7339g3fg.pdf

SmellyCode++: Multi-Label Dataset for Code Smell Detection.

Authors: Alomari, Nawaf Alazba, Amal Aljamaan, Hamoud et al.

Source: Scientific Data; 7/12/2025, Vol. 12 Issue 1, p1-15, 15p

Subject Terms: MAINTAINABILITY (Engineering), SOFTWARE refactoring, SOFTWARE architecture, FEATURE extraction, DATA structures, COMPUTER software development

An Approach Based on Sum Product Networks for Code Smells Detection.

Authors: Abdelkader, Mostefai

Source: Journal of Communications Software & Systems; Jun2025, Vol. 21 Issue 2, p189-200, 12p

Subject Terms: MACHINE learning, DISTRIBUTION (Probability theory), LINEAR network coding, SOFTWARE engineering, PRODUCT coding

A Novel Approach for Enhancing Code Smell Detection Using Random Convolutional Kernel Transform.

Authors: Abdelkader, Mostefai Mansour, Mekour

Source: e-Informatica; 2025, Vol. 19 Issue 1, p1-32, 32p

Subject Terms: SOFTWARE engineering, DEEP learning, MACHINE learning, EMPIRICAL research, SIGNAL detection, DEFECT tracking (Computer software development), FEATURE selection

Automated Detection of Code Smells for Machine Learning Applications

Authors: Zhang, Haiyin (author)

Index Terms: Software Quality, Static Code Analysis, Machine Learning, Technical Debt, master thesis

URL: http://resolver.tudelft.nl/uuid:bd2b288e-08f9-4200-92c8-ee48bfff9408