Image de couverture de livre

SATDAUG -- A Balanced and Augmented Dataset for Detecting Self-Admitted Technical Debt

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Sutoyo, Edi, Capiluppi, Andrea
Format:	Preprint
Publié:	2024
Sujets:	Software Engineering Computation and Language
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Self-Admitted Technical Debt Detection Approaches: A Decade Systematic Review
par: Sutoyo, Edi, et autres
Publié: (2023)

Deep Learning and Data Augmentation for Detecting Self-Admitted Technical Debt
par: Sutoyo, Edi, et autres
Publié: (2024)

Self‐Admitted Technical Debt Detection Approaches: A Decade Systematic Review
par: Edi Sutoyo, et autres
Publié: (2026)

The Dangers of Non-Self-Fixed Architecture Technical Debt and Its Impact on Time-to-Fix
par: Sutoyo, Edi, et autres
Publié: (2026)

Reducing Labeling Effort in Architecture Technical Debt Detection through Active Learning and Explainable AI
par: Sutoyo, Edi, et autres
Publié: (2026)

Tracing the Lifecycle of Architecture Technical Debt in Software Systems: A Dependency Approach
par: Sutoyo, Edi, et autres
Publié: (2025)

Development and Adoption of SATD Detection Tools: A State-of-practice Report
par: Sutoyo, Edi, et autres
Publié: (2024)

Hidden in Plain Sight: Where Developers Confess Self-Admitted Technical Debt
par: Sridharan, Murali, et autres
Publié: (2025)

Descriptor: C++ Self-Admitted Technical Debt Dataset (CppSATD)
par: Pham, Phuoc, et autres
Publié: (2025)

Exploring the Advances in Using Machine Learning to Identify Technical Debt and Self-Admitted Technical Debt
par: Melin, Eric L., et autres
Publié: (2024)

A First Look at the Self-Admitted Technical Debt in Test Code: Taxonomy and Detection
par: Islam, Shahidul, et autres
Publié: (2025)

A Taxonomy of Self-Admitted Technical Debt in Deep Learning Systems
par: Pepe, Federica, et autres
Publié: (2024)

Quantifying and Characterizing Clones of Self-Admitted Technical Debt in Build Systems
par: Xiao, Tao, et autres
Publié: (2024)

Understanding Self-Admitted Technical Debt in Test Code: An Empirical Study
par: Nakamura, Ibuki, et autres
Publié: (2025)

Negativity in Self-Admitted Technical Debt: How Sentiment Influences Prioritization
par: Cassee, Nathan, et autres
Publié: (2025)

An Empirical Study of Self-Admitted Technical Debt in Machine Learning Software
par: Bhatia, Aaditya, et autres
Publié: (2023)

Multi-Artifact Analysis of Self-Admitted Technical Debt in Scientific Software
par: Melin, Eric L., et autres
Publié: (2026)

A First Look at the Lifecycle of DL-Specific Self-Admitted Technical Debt
par: Recupito, Gilberto, et autres
Publié: (2025)

Self-Admitted Technical Debt in Scientific Software: Prioritization, Sentiment, and Propagation Across Artifacts
par: Melin, Eric L., et autres
Publié: (2026)

What Can Self-Admitted Technical Debt Tell Us About Security? A Mixed-Methods Study
par: Ferreyra, Nicolás E. Díaz, et autres
Publié: (2024)

Reading Between the Code Lines: On the Use of Self-Admitted Technical Debt for Security Analysis
par: Ferreyra, Nicolás E. Díaz, et autres
Publié: (2026)

Self-Admitted Technical Debt in LLM Software: An Empirical Comparison with ML and Non-ML Software
par: Selvanayagam, Niruthiha, et autres
Publié: (2026)

How Do Community Smells Influence Self-Admitted Technical Debt in Machine Learning Projects?
par: Cynthia, Shamse Tasnim, et autres
Publié: (2025)

Understanding the Effectiveness of LLMs in Automated Self-Admitted Technical Debt Repayment
par: Sheikhaei, Mohammad Sadegh, et autres
Publié: (2025)

Evidence is All We Need: Do Self-Admitted Technical Debts Impact Method-Level Maintenance?
par: Chowdhury, Shaiful, et autres
Publié: (2024)

Text Tells the Cost: Predicting and Analyzing Repayment Effort of Self-Admitted Technical Debt
par: Li, Yikun, et autres
Publié: (2023)

"TODO: Fix the Mess Gemini Created": Towards Understanding GenAI-Induced Self-Admitted Technical Debt
par: Mujahid, Abdullah Al, et autres
Publié: (2026)

Detection, Classification and Prevalence of Self-Admitted Aging Debt
par: Sridharan, Murali, et autres
Publié: (2025)

Automatic Bottom-Up Taxonomy Construction: A Software Application Domain Study
par: Sas, Cezar, et autres
Publié: (2024)

AutoFL: A Tool for Automatic Multi-granular Labelling of Software Repositories
par: Sas, Cezar, et autres
Publié: (2024)

Different Debt: An Addition to the Technical Debt Dataset and a Demonstration Using Developer Personality
par: Graf-Vlachy, Lorenz, et autres
Publié: (2024)

Detection of Technical Debt in Java Source Code
par: Hai, Nam Le, et autres
Publié: (2024)

TagDebt: A Bot to Support Technical Debt Management
par: Biazotto, João Paulo, et autres
Publié: (2026)

The TechDebt Game -- Enabling Discussions about Technical Debt
par: Wiese, Marion, et autres
Publié: (2025)

Machine Learning Models for the Early Detection of Burnout in Software Engineering: a Systematic Literature Review
par: Tulili, Tien Rahayu, et autres
Publié: (2026)

Technical Lag as Latent Technical Debt: A Rapid Review
par: Panter, Shane K., et autres
Publié: (2026)

The Technical Debt Gamble: A Case Study on Technical Debt in a Large-Scale Industrial Microservice Architecture
par: Borowa, Klara, et autres
Publié: (2025)

PromptDebt: A Comprehensive Study of Technical Debt Across LLM Projects
par: Aljohani, Ahmed, et autres
Publié: (2025)

Benchmarking Failures in Tool-Augmented Language Models
par: Treviño, Eduardo, et autres
Publié: (2025)

Refining GPT-3 Embeddings with a Siamese Structure for Technical Post Duplicate Detection
par: Wu, Xingfang, et autres
Publié: (2023)