How Do Communities of ML-Enabled Systems Smell? A Cross-Sectional Study on the Prevalence of Community Smells
Fuente:
arXiv
Saved in:
| Main Authors: | Annunziata, Giusy, Lambiase, Stefano, Palomba, Fabio, Catolino, Gemma, Ferrucci, Filomena |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Socio-Technical Well-Being of Quantum Software Communities: An Overview on Community Smells
by: Lambiase, Stefano, et al.
Published: (2026)
by: Lambiase, Stefano, et al.
Published: (2026)
Motivations, Challenges, Best Practices, and Benefits for Bots and Conversational Agents in Software Engineering: A Multivocal Literature Review
by: Lambiase, Stefano, et al.
Published: (2024)
by: Lambiase, Stefano, et al.
Published: (2024)
When Code Smells Meet ML: On the Lifecycle of ML-specific Code Smells in ML-enabled Systems
by: Recupito, Gilberto, et al.
Published: (2024)
by: Recupito, Gilberto, et al.
Published: (2024)
Exploring Individual Factors in the Adoption of LLMs for Specific Software Engineering Purposes
by: Lambiase, Stefano, et al.
Published: (2025)
by: Lambiase, Stefano, et al.
Published: (2025)
Investigating the Role of Cultural Values in Adopting Large Language Models for Software Engineering
by: Lambiase, Stefano, et al.
Published: (2024)
by: Lambiase, Stefano, et al.
Published: (2024)
From Expectation to Habit: Why Do Software Practitioners Adopt Fairness Toolkits?
by: Voria, Gianmario, et al.
Published: (2024)
by: Voria, Gianmario, et al.
Published: (2024)
Sustainability of Machine Learning-Enabled Systems: The Machine Learning Practitioner's Perspective
by: De Martino, Vincenzo, et al.
Published: (2025)
by: De Martino, Vincenzo, et al.
Published: (2025)
Contextual Fairness-Aware Practices in ML: A Cost-Effective Empirical Evaluation
by: Parziale, Alessandra, et al.
Published: (2025)
by: Parziale, Alessandra, et al.
Published: (2025)
A Catalog of Fairness-Aware Practices in Machine Learning Engineering
by: Voria, Gianmario, et al.
Published: (2024)
by: Voria, Gianmario, et al.
Published: (2024)
How Do Community Smells Influence Self-Admitted Technical Debt in Machine Learning Projects?
by: Cynthia, Shamse Tasnim, et al.
Published: (2025)
by: Cynthia, Shamse Tasnim, et al.
Published: (2025)
Performance Smells in ML and Non-ML Python Projects: A Comparative Study
by: Belias, François, et al.
Published: (2025)
by: Belias, François, et al.
Published: (2025)
Do Prompt Patterns Affect Code Quality? A First Empirical Assessment of ChatGPT-Generated Code
by: Della Porta, Antonio, et al.
Published: (2025)
by: Della Porta, Antonio, et al.
Published: (2025)
Investigating the Performance of Small Language Models in Detecting Test Smells in Manual Test Cases
by: Lucas, Keila, et al.
Published: (2025)
by: Lucas, Keila, et al.
Published: (2025)
Do Developers Adopt Green Architectural Tactics for ML-Enabled Systems? A Mining Software Repository Study
by: De Martino, Vincenzo, et al.
Published: (2024)
by: De Martino, Vincenzo, et al.
Published: (2024)
Smells Depend on the Context: An Interview Study of Issue Tracking Problems and Smells in Practice
by: Montgomery, Lloyd, et al.
Published: (2026)
by: Montgomery, Lloyd, et al.
Published: (2026)
RECOVER: Toward Requirements Generation from Stakeholders' Conversations
by: Voria, Gianmario, et al.
Published: (2024)
by: Voria, Gianmario, et al.
Published: (2024)
The Role of the Retrospective Meetings in Detecting, Refactoring and Monitoring Community Smells
by: Dantas, Carlos, et al.
Published: (2025)
by: Dantas, Carlos, et al.
Published: (2025)
ML Code Smells: From Specification to Detection
by: Mahmoudi, Brahim, et al.
Published: (2025)
by: Mahmoudi, Brahim, et al.
Published: (2025)
On the Prevalence, Evolution, and Impact of Code Smells in Simulation Modelling Software
by: Mahbub, Riasat, et al.
Published: (2024)
by: Mahbub, Riasat, et al.
Published: (2024)
Characterizing Requirements Smells
by: Gentili, Emanuele, et al.
Published: (2024)
by: Gentili, Emanuele, et al.
Published: (2024)
Tracing Stereotypes in Pre-trained Transformers: From Biased Neurons to Fairer Models
by: Voria, Gianmario, et al.
Published: (2026)
by: Voria, Gianmario, et al.
Published: (2026)
An Event-Driven Tool for Context-Aware Code Smell Detection Using SmellDSL
by: Viegas, Matheus dos Santos, et al.
Published: (2026)
by: Viegas, Matheus dos Santos, et al.
Published: (2026)
SCOPE: A Dataset of Stereotyped Prompts for Counterfactual Fairness Assessment of LLMs
by: Parziale, Alessandra, et al.
Published: (2026)
by: Parziale, Alessandra, et al.
Published: (2026)
Data Preparation for Fairness-Performance Trade-Offs: A Practitioner-Friendly Alternative?
by: Voria, Gianmario, et al.
Published: (2024)
by: Voria, Gianmario, et al.
Published: (2024)
Comparing ML-Specific and General Python Code Smells Across Project Characteristics
by: Agh, Halimeh, et al.
Published: (2026)
by: Agh, Halimeh, et al.
Published: (2026)
Classification, Challenges, and Automated Approaches to Handle Non-Functional Requirements in ML-Enabled Systems: A Systematic Literature Review
by: De Martino, Vincenzo, et al.
Published: (2023)
by: De Martino, Vincenzo, et al.
Published: (2023)
Toward Systematic Counterfactual Fairness Evaluation of Large Language Models: The CAFFE Framework
by: Parziale, Alessandra, et al.
Published: (2025)
by: Parziale, Alessandra, et al.
Published: (2025)
Empirical Study of the Docker Smells Impact on the Image Size
by: Durieux, Thomas
Published: (2023)
by: Durieux, Thomas
Published: (2023)
A Validated Taxonomy on Software Energy Smells
by: Mehditabar, Mohammadjavad, et al.
Published: (2026)
by: Mehditabar, Mohammadjavad, et al.
Published: (2026)
Bias Ahead: Sensitive Prompts as Early Warnings for Fairness in Large Language Models
by: Voria, Gianmario, et al.
Published: (2026)
by: Voria, Gianmario, et al.
Published: (2026)
Agentic LMs: Hunting Down Test Smells
by: Melo, Rian, et al.
Published: (2025)
by: Melo, Rian, et al.
Published: (2025)
Towards a Taxonomy of Software Log Smells
by: Saarimäki, Nyyti, et al.
Published: (2024)
by: Saarimäki, Nyyti, et al.
Published: (2024)
xNose: A Test Smell Detector for C#
by: Paul, Partha P., et al.
Published: (2024)
by: Paul, Partha P., et al.
Published: (2024)
Smells-sus: Sustainability Smells in IaC
by: Kosbar, Seif, et al.
Published: (2025)
by: Kosbar, Seif, et al.
Published: (2025)
Once Upon a Team: Investigating Bias in LLM-Driven Software Team Composition and Task Allocation
by: Parziale, Alessandra, et al.
Published: (2026)
by: Parziale, Alessandra, et al.
Published: (2026)
FedCSD: A Federated Learning Based Approach for Code-Smell Detection
by: Alawadi, Sadi, et al.
Published: (2023)
by: Alawadi, Sadi, et al.
Published: (2023)
How Propense Are Large Language Models at Producing Code Smells? A Benchmarking Study
by: Velasco, Alejandro, et al.
Published: (2024)
by: Velasco, Alejandro, et al.
Published: (2024)
Evaluating LLMs Effectiveness in Detecting and Correcting Test Smells: An Empirical Study
by: Santana Jr, E. G., et al.
Published: (2025)
by: Santana Jr, E. G., et al.
Published: (2025)
Green Architectural Tactics in ML-enabled Systems: An LLM-based Repository Mining Study
by: De Martino, Vincenzo, et al.
Published: (2026)
by: De Martino, Vincenzo, et al.
Published: (2026)
On the Impact of 3D Visualization of Repository Metrics in Software Engineering Education
by: Di Dario, Dario, et al.
Published: (2024)
by: Di Dario, Dario, et al.
Published: (2024)
Similar Items
-
Socio-Technical Well-Being of Quantum Software Communities: An Overview on Community Smells
by: Lambiase, Stefano, et al.
Published: (2026) -
Motivations, Challenges, Best Practices, and Benefits for Bots and Conversational Agents in Software Engineering: A Multivocal Literature Review
by: Lambiase, Stefano, et al.
Published: (2024) -
When Code Smells Meet ML: On the Lifecycle of ML-specific Code Smells in ML-enabled Systems
by: Recupito, Gilberto, et al.
Published: (2024) -
Exploring Individual Factors in the Adoption of LLMs for Specific Software Engineering Purposes
by: Lambiase, Stefano, et al.
Published: (2025) -
Investigating the Role of Cultural Values in Adopting Large Language Models for Software Engineering
by: Lambiase, Stefano, et al.
Published: (2024)