Cover Image

Detection of Technical Debt in Java Source Code

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Hai, Nam Le, Bui, Anh M. T., Nguyen, Phuong T., Di Ruscio, Davide, Kazman, Rick
Format:	Preprint
Published:	2024
Subjects:	Software Engineering
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Good things come in three: Generating SO Post Titles with Pre-Trained Models, Self Improvement and Post Ranking
by: Le, Duc Anh, et al.
Published: (2024)

Bake Two Cakes with One Oven: RL for Defusing Popularity Bias and Cold-start in Third-Party Library Recommendations
by: Vuong, Minh Hoang, et al.
Published: (2025)

Detecting Malicious Source Code in PyPI Packages with LLMs: Does RAG Come in Handy?
by: Ibiyo, Motunrayo, et al.
Published: (2025)

When simplicity meets effectiveness: Detecting code comments coherence with word embeddings and LSTM
by: Igbomezie, Michael Dubem, et al.
Published: (2024)

Larger Is Not Always Better: Leveraging Structured Code Diffs for Comment Inconsistency Detection
by: Nguyen, Phong, et al.
Published: (2025)

Many Hands Make Light Work: An LLM-based Multi-Agent System for Detecting Malicious PyPI Packages
by: Zeshan, Muhammad Umar, et al.
Published: (2026)

EnseSmells: Deep ensemble and programming language models for automated code smells detection
by: Ho, Anh, et al.
Published: (2025)

On the use of Large Language Models in Model-Driven Engineering
by: Di Rocco, Juri, et al.
Published: (2024)

Automated categorization of pre-trained models for software engineering: A case study with a Hugging Face dataset
by: Di Sipio, Claudio, et al.
Published: (2024)

Teamwork makes the dream work: LLMs-Based Agents for GitHub README.MD Summarization
by: Nguyen, Duc S. H., et al.
Published: (2025)

Do Not Treat Code as Natural Language: Implications for Repository-Level Code Generation and Beyond
by: Le-Anh, Minh, et al.
Published: (2026)

When Retriever Meets Generator: A Joint Model for Code Comment Generation
by: Le, Tien P. T., et al.
Published: (2025)

Automatic Categorization of GitHub Actions with Transformers and Few-shot Learning
by: Nguyen, Phuong T., et al.
Published: (2024)

On the Impacts of Contexts on Repository-Level Code Generation
by: Hai, Nam Le, et al.
Published: (2024)

CodeMMLU: A Multi-Task Benchmark for Assessing Code Understanding & Reasoning Capabilities of CodeLLMs
by: Manh, Dung Nguyen, et al.
Published: (2024)

Technical Debt and Code Migration
by: Holland, John Gerrard
Published: (2025)

CodeWiki: Evaluating AI's Ability to Generate Holistic Documentation for Large-Scale Codebases
by: Hoang, Anh Nguyen, et al.
Published: (2025)

Evaluating Time-Dependent Methods and Seasonal Effects in Code Technical Debt Prediction
by: Robredo, Mikel, et al.
Published: (2024)

Practitioner Views on Mobile App Accessibility: Practices and Challenges
by: Indika, Amila, et al.
Published: (2026)

A First Look at the Self-Admitted Technical Debt in Test Code: Taxonomy and Detection
by: Islam, Shahidul, et al.
Published: (2025)

Addressing Popularity Bias in Third-Party Library Recommendations Using LLMs
by: Di Sipio, Claudio, et al.
Published: (2025)

Automation in Model-Driven Engineering: A look back, and ahead
by: Burgueño, Lola, et al.
Published: (2024)

Oops!... I did it again. Conclusion (In-)Stability in Quantitative Empirical Software Engineering: A Large-Scale Analysis
by: Hoess, Nicole, et al.
Published: (2025)

Leveraging Sustainable Systematic Literature Reviews
by: Santos, Vinicius dos, et al.
Published: (2025)

Does the Tool Matter? Exploring Some Causes of Threats to Validity in Mining Software Repositories
by: Hoess, Nicole, et al.
Published: (2025)

Understanding Self-Admitted Technical Debt in Test Code: An Empirical Study
by: Nakamura, Ibuki, et al.
Published: (2025)

Investigating Issues that Lead to Code Technical Debt in Machine Learning Systems
by: Ximenes, Rodrigo, et al.
Published: (2025)

Exploring the Relationship Between Ownership and Contribution Alignment and Code Technical Debt
by: Zabardast, Ehsan, et al.
Published: (2023)

Qualitative Coding Analysis through Open-Source Large Language Models: A User Study and Design Recommendations
by: Ngo, Tung T., et al.
Published: (2026)

How fair are we? From conceptualization to automated assessment of fairness definitions
by: d'Aloisio, Giordano, et al.
Published: (2024)

Documentation-Guided Agentic Codebase Migration from C to Rust
by: Le-Anh, Minh, et al.
Published: (2026)

TagDebt: A Bot to Support Technical Debt Management
by: Biazotto, João Paulo, et al.
Published: (2026)

The TechDebt Game -- Enabling Discussions about Technical Debt
by: Wiese, Marion, et al.
Published: (2025)

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

Explaining the Contributing Factors for Vulnerability Detection in Machine Learning
by: Mouine, Esma, et al.
Published: (2024)

DocChecker: Bootstrapping Code Large Language Model for Detecting and Resolving Code-Comment Inconsistencies
by: Dau, Anh T. V., et al.
Published: (2023)

The Nature of Technical Debt in Research Software
by: Ernst, Neil A., et al.
Published: (2026)

A Taxonomy of Self-Admitted Technical Debt in Deep Learning Systems
by: Pepe, Federica, et al.
Published: (2024)

The Technical Debt Gamble: A Case Study on Technical Debt in a Large-Scale Industrial Microservice Architecture
by: Borowa, Klara, et al.
Published: (2025)

Technical Lag as Latent Technical Debt: A Rapid Review
by: Panter, Shane K., et al.
Published: (2026)