Imagen de Portada

PyExamine A Comprehensive, UnOpinionated Smell Detection Tool for Python

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Shivashankar, Karthik, Martini, Antonio
Formato:	Preprint
Publicado:	2025
Materias:	Software Engineering
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Better Python Programming for all: With the focus on Maintainability
por: Shivashankar, Karthik, et al.
Publicado: (2024)

Maintainability Challenges in ML: A Systematic Literature Review
por: Shivashankar, Karthik, et al.
Publicado: (2024)

MLScent A tool for Anti-pattern detection in ML projects
por: Shivashankar, Karthik, et al.
Publicado: (2025)

TD-Suite: All Batteries Included Framework for Technical Debt Classification
por: Shivashankar, Karthik, et al.
Publicado: (2025)

Unravelling Technical debt topics through Time, Programming Languages and Repository
por: Shivashankar, Karthik, et al.
Publicado: (2025)

Scalability and Maintainability Challenges and Solutions in Machine Learning: Systematic Literature Review
por: Shivashankar, Karthik, et al.
Publicado: (2025)

Identifying Technical Debt and Its Types Across Diverse Software Projects Issues
por: Shivashankar, Karthik, et al.
Publicado: (2024)

FauxPy: A Fault Localization Tool for Python
por: Rezaalipour, Mohammad, et al.
Publicado: (2024)

An Event-Driven Tool for Context-Aware Code Smell Detection Using SmellDSL
por: Viegas, Matheus dos Santos, et al.
Publicado: (2026)

QualiTagger: Automating software quality detection in issue trackers
por: Shivashankar, Karthik, et al.
Publicado: (2025)

PyTrim: A Practical Tool for Reducing Python Dependency Bloat
por: Karakatsanis, Konstantinos, et al.
Publicado: (2025)

TypeEvalPy: A Micro-benchmarking Framework for Python Type Inference Tools
por: Venkatesh, Ashwin Prasad Shivarpatna, et al.
Publicado: (2023)

PyGress: Tool for Analyzing the Progression of Code Proficiency in Python OSS Projects
por: Charatvaraphan, Rujiphart, et al.
Publicado: (2025)

A Comprehensive Evaluation of Parameter-Efficient Fine-Tuning on Code Smell Detection
por: Zhang, Beiqi, et al.
Publicado: (2024)

Performance Smells in ML and Non-ML Python Projects: A Comparative Study
por: Belias, François, et al.
Publicado: (2025)

Comparing ML-Specific and General Python Code Smells Across Project Characteristics
por: Agh, Halimeh, et al.
Publicado: (2026)

DyPyBench: A Benchmark of Executable Python Software
por: Bouzenia, Islem, et al.
Publicado: (2024)

PyTy: Repairing Static Type Errors in Python
por: Chow, Yiu Wai, et al.
Publicado: (2024)

From Code Smells to Best Practices: Tackling Resource Leaks in PyTorch, TensorFlow, and Keras
por: Abdallah, Bashar, et al.
Publicado: (2025)

SafePyScript: A Web-Based Solution for Machine Learning-Driven Vulnerability Detection in Python
por: Farasat, Talaya, et al.
Publicado: (2024)

Cache-Related Smells in GitLab CI/CD: Comprehensive Catalog, Automated Detection, and Empirical Evidence
por: Urdih, Francesco, et al.
Publicado: (2026)

PyTracer: Automatically profiling numerical instabilities in Python
por: Chatelain, Yohan, et al.
Publicado: (2021)

HaPy-Bug -- Human Annotated Python Bug Resolution Dataset
por: Przymus, Piotr, et al.
Publicado: (2025)

Towards Automated Detection of Inline Code Comment Smells
por: Oztas, Ipek, et al.
Publicado: (2025)

Evaluating Large Language Models in Detecting Test Smells
por: Lucas, Keila, et al.
Publicado: (2024)

An Empirical Evaluation of Code Smell Detection in Angular Applications
por: Nunes, Maykon, et al.
Publicado: (2026)

PyPulse: A Python Library for Biosignal Imputation
por: Gao, Kevin, et al.
Publicado: (2024)

HQPEF-Py: Metrics, Python Patterns, and Guidance for Evaluating Hybrid Quantum Programs
por: Osei, Michael Adjei, et al.
Publicado: (2025)

Less is More? An Empirical Study on Configuration Issues in Python PyPI Ecosystem
por: Peng, Yun, et al.
Publicado: (2023)

Copilot-in-the-Loop: Fixing Code Smells in Copilot-Generated Python Code using Copilot
por: Zhang, Beiqi, et al.
Publicado: (2024)

The Role of the Retrospective Meetings in Detecting, Refactoring and Monitoring Community Smells
por: Dantas, Carlos, et al.
Publicado: (2025)

Characterizing Requirements Smells
por: Gentili, Emanuele, et al.
Publicado: (2024)

Smells Depend on the Context: An Interview Study of Issue Tracking Problems and Smells in Practice
por: Montgomery, Lloyd, et al.
Publicado: (2026)

Prompt Learning for Multi-Label Code Smell Detection: A Promising Approach
por: Liu, Haiyang, et al.
Publicado: (2024)

Specification and Detection of LLM Code Smells
por: Mahmoudi, Brahim, et al.
Publicado: (2025)

Evaluating LLMs Effectiveness in Detecting and Correcting Test Smells: An Empirical Study
por: Santana Jr, E. G., et al.
Publicado: (2025)

BugsInPy: A Database of Existing Bugs in Python Programs to Enable Controlled Testing and Debugging Studies
por: Widyasari, Ratnadira, et al.
Publicado: (2024)

How Do Communities of ML-Enabled Systems Smell? A Cross-Sectional Study on the Prevalence of Community Smells
por: Annunziata, Giusy, et al.
Publicado: (2025)

From Code Changes to Quality Gains: An Empirical Study in Python ML Systems with PyQu
por: Almukhtar, Mohamed, et al.
Publicado: (2025)

A Validated Taxonomy on Software Energy Smells
por: Mehditabar, Mohammadjavad, et al.
Publicado: (2026)