Cover Image

COBOLAssist: Analyzing and Fixing Compilation Errors for LLM-Powered COBOL Code Generation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Dau, Anh T. V., Tan, Shin Hwei, Yang, Jinqiu, Bui, Nghi D. Q., Nguyen, Anh Tuan
Format:	Preprint
Published:	2026
Subjects:	Software Engineering Programming Languages
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

COBOL-Coder: Domain-Adapted Large Language Models for COBOL Code Generation and Translation
by: Dau, Anh T. V., et al.
Published: (2026)

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

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

Envisioning the Next-Generation AI Coding Assistants: Insights & Proposals
by: Nghiem, Khanh, et al.
Published: (2024)

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

Structured Safety Auditing for Balancing Code Correctness and Content Safety in LLM-Generated Code
by: Tan, Honghao, et al.
Published: (2026)

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

LLM-Guided Issue Generation from Uncovered Code Segments
by: Pressato, Diany, et al.
Published: (2026)

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

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

Functional Overlap Reranking for Neural Code Generation
by: To, Hung Quoc, et al.
Published: (2023)

Agentic Coding Needs Proactivity, Not Just Autonomy
by: Bui, Nghi D. Q., et al.
Published: (2026)

Guiding ChatGPT to Fix Web UI Tests via Explanation-Consistency Checking
by: Xu, Zhuolin, et al.
Published: (2023)

An Empirical Study of False Negatives and Positives of Static Code Analyzers From the Perspective of Historical Issues
by: Cui, Han, et al.
Published: (2024)

Understanding and Detecting Annotation-Induced Faults of Static Analyzers
by: Zhang, Huaien, et al.
Published: (2024)

Investigating Code Reuse in Software Redesign: A Case Study
by: Zhang, Xiaowen, et al.
Published: (2026)

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)

Testing Refactoring Engine via Historical Bug Report driven LLM
by: Wang, Haibo, et al.
Published: (2025)

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

CodeLSI: Leveraging Foundation Models for Automated Code Generation with Low-Rank Optimization and Domain-Specific Instruction Tuning
by: Le, Huy, et al.
Published: (2025)

What Makes Code Generation Ethically Sourced?
by: Xu, Zhuolin, et al.
Published: (2025)

LPR: Large Language Models-Aided Program Reduction
by: Zhang, Mengxiao, et al.
Published: (2023)

HyperAgent: Generalist Software Engineering Agents to Solve Coding Tasks at Scale
by: Phan, Huy Nhat, et al.
Published: (2024)

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

Model-Agnostic Correctness Assessment for LLM-Generated Code via Dynamic Internal Representation Selection
by: Vu, Thanh Trong, et al.
Published: (2025)

Automated Harmfulness Testing for Code Large Language Models
by: Tan, Honghao, et al.
Published: (2025)

CodeFlow: Program Behavior Prediction with Dynamic Dependencies Learning
by: Le, Cuong Chi, et al.
Published: (2024)

CodeArena: A Collective Evaluation Platform for LLM Code Generation
by: Du, Mingzhe, et al.
Published: (2025)

A Multi-Language Perspective on the Robustness of LLM Code Generation
by: Rabbi, Fazle, et al.
Published: (2025)

Quality Evaluation of COBOL to Java Code Transformation
by: Froimovich, Shmulik, et al.
Published: (2025)

RepoHyper: Search-Expand-Refine on Semantic Graphs for Repository-Level Code Completion
by: Phan, Huy N., et al.
Published: (2024)

Finding Compiler Bugs through Cross-Language Code Generator and Differential Testing
by: Feng, Qiong, et al.
Published: (2025)

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

BloomAPR: A Bloom's Taxonomy-based Framework for Assessing the Capabilities of LLM-Powered APR Solutions
by: Ma, Yinghang, et al.
Published: (2025)

Detection of Technical Debt in Java Source Code
by: Hai, Nam Le, et al.
Published: (2024)

Bias Unveiled: Investigating Social Bias in LLM-Generated Code
by: Ling, Lin, et al.
Published: (2024)

Dissecting Bug Triggers and Failure Modes in Modern Agentic Frameworks: An Empirical Study
by: Zhang, Xiaowen, et al.
Published: (2026)

iML: Executable, Problem-Grounded, and Broadly Exploratory Code-Driven AutoML
by: Le, Dat, et al.
Published: (2026)

Ethics Testing: Proactive Identification of Generative AI System Harms
by: Tan, Shin Hwei, et al.
Published: (2026)

Demystifying Errors in LLM Reasoning Traces: An Empirical Study of Code Execution Simulation
by: Abdollahi, Mohammad, et al.
Published: (2025)