Image de couverture de livre

An Empirical Evaluation of Pre-trained Large Language Models for Repairing Declarative Formal Specifications

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Alhanahnah, Mohannad, Hasan, Md Rashedul, Xu, Lisong, Bagheri, Hamid
Format:	Preprint
Publié:	2024
Sujets:	Software Engineering
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

DepsRAG: Towards Agentic Reasoning and Planning for Software Dependency Management
par: Alhanahnah, Mohannad, et autres
Publié: (2024)

SoK: Software Debloating Landscape and Future Directions
par: Alhanahnah, Mohannad, et autres
Publié: (2024)

The Cure is in the Cause: A Filesystem for Container Debloating
par: Zhang, Huaifeng, et autres
Publié: (2023)

Practical Program Repair in the Era of Large Pre-trained Language Models
par: Xia, Chunqiu Steven, et autres
Publié: (2022)

Empirical Evaluation of Large Language Models in Automated Program Repair
par: Sun, Jiajun, et autres
Publié: (2025)

LLM-CompDroid: Repairing Configuration Compatibility Bugs in Android Apps with Pre-trained Large Language Models
par: Liu, Zhijie, et autres
Publié: (2024)

Improving the Ability of Pre-trained Language Model by Imparting Large Language Model's Experience
par: Yin, Xin, et autres
Publié: (2024)

BACFuzz: Exposing the Silence on Broken Access Control Vulnerabilities in Web Applications
par: Dharmaadi, I Putu Arya, et autres
Publié: (2025)

On the Evaluation of Large Language Models in Multilingual Vulnerability Repair
par: wang, Dong, et autres
Publié: (2025)

SpecGen: Automated Generation of Formal Program Specifications via Large Language Models
par: Ma, Lezhi, et autres
Publié: (2024)

Automated Repair of AI Code with Large Language Models and Formal Verification
par: Charalambous, Yiannis, et autres
Publié: (2024)

Automated Program Repair Based on REST API Specifications Using Large Language Models
par: Yamagishi, Katsuki, et autres
Publié: (2025)

Can Large Language Models Model Programs Formally?
par: Chen, Zhiyong, et autres
Publié: (2026)

Natural Is The Best: Model-Agnostic Code Simplification for Pre-trained Large Language Models
par: Wang, Yan, et autres
Publié: (2024)

Machine Learning Systems are Bloated and Vulnerable
par: Zhang, Huaifeng, et autres
Publié: (2022)

Assessing Small Language Models for Code Generation: An Empirical Study with Benchmarks
par: Hasan, Md Mahade, et autres
Publié: (2025)

Crash Report Enhancement with Large Language Models: An Empirical Study
par: Fahim, S M Farah Al, et autres
Publié: (2025)

An Empirical Study of Python Library Migration Using Large Language Models
par: Islam, Md Mohayeminul, et autres
Publié: (2025)

Ensembling Large Language Models for Code Vulnerability Detection: An Empirical Evaluation
par: Sun, Zhihong, et autres
Publié: (2025)

SiblingRepair: Sibling-Based Multi-Hunk Repair with Large Language Models
par: Liu, Xinyu, et autres
Publié: (2026)

An Agile Formal Specification Language Design Based on K Framework
par: Zhang, Jianyu, et autres
Publié: (2024)

VulnRepairEval: An Exploit-Based Evaluation Framework for Assessing Large Language Model Vulnerability Repair Capabilities
par: Wang, Weizhe, et autres
Publié: (2025)

An Empirical Evaluation of LLM-Based Approaches for Code Vulnerability Detection: RAG, SFT, and Dual-Agent Systems
par: Saju, Md Hasan, et autres
Publié: (2026)

How Small is Enough? Empirical Evidence of Quantized Small Language Models for Automated Program Repair
par: Kusama, Kazuki, et autres
Publié: (2025)

Handling Open-Vocabulary Constructs in Formalizing Specifications: Retrieval-Augmented Parsing with Expert Knowledge
par: Hasan, Mohammad Saqib, et autres
Publié: (2025)

SpecEval: Evaluating Code Comprehension in Large Language Models via Program Specifications
par: Ma, Lezhi, et autres
Publié: (2024)

Cross-Task Benchmarking and Evaluation of General-Purpose and Code-Specific Large Language Models
par: Das, Gunjan, et autres
Publié: (2025)

LEANCODE: Understanding Models Better for Code Simplification of Pre-trained Large Language Models
par: Wang, Yan, et autres
Publié: (2025)

Model Compression vs. Adversarial Robustness: An Empirical Study on Language Models for Code
par: Awal, Md. Abdul, et autres
Publié: (2025)

FeedbackEval: A Benchmark for Evaluating Large Language Models in Feedback-Driven Code Repair Tasks
par: Dai, Dekun, et autres
Publié: (2025)

On the Effectiveness of Large Language Models in Domain-Specific Code Generation
par: Gu, Xiaodong, et autres
Publié: (2023)

Automatic High-Level Test Case Generation using Large Language Models
par: Hasan, Navid Bin, et autres
Publié: (2025)

A Pilot Study on Detecting Software Design Patterns with Large Language Models: An Empirical Evaluation
par: Chowdhury, Oishik, et autres
Publié: (2026)

Automated Repair of C Programs Using Large Language Models
par: Farzandway, Mahdi, et autres
Publié: (2025)

Exploring Generalizable Automated Program Repair with Large Language Models
par: Campos, Viola, et autres
Publié: (2025)

Bridge and Hint: Extending Pre-trained Language Models for Long-Range Code
par: Chen, Yujia, et autres
Publié: (2024)

Repair Ingredients Are All You Need: Improving Large Language Model-Based Program Repair via Repair Ingredients Search
par: Zhang, Jiayi, et autres
Publié: (2025)

Large Language Models for Fault Localization: An Empirical Study
par: Xiao, YingJian, et autres
Publié: (2025)

Event-B Agent: Towards LLM Agent for Formal Model Synthesis and Repair
par: Wang, Hongshu, et autres
Publié: (2026)

From Online User Feedback to Requirements: Evaluating Large Language Models for Classification and Specification Tasks
par: Mallya, Manjeshwar Aniruddh, et autres
Publié: (2025)