Copertina

A Tertiary Review of Large Language Model-Based Code Generating Tasks: Trends, Challenges, and Future Directions

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Chochlov, Muslim, English, Michael, Buckley, Jim
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Software Engineering Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Using Changeset Descriptions as a Data Source to Assist Feature Location
di: Chochlov, Muslim, et al.
Pubblicazione: (2024)

Selecting and Combining Large Language Models for Scalable Code Clone Detection
di: Chochlov, Muslim, et al.
Pubblicazione: (2025)

Task Abstention for Large Language Models in Code Generation
di: Zhou, Yanke, et al.
Pubblicazione: (2026)

GeoCode-GPT: A Large Language Model for Geospatial Code Generation Tasks
di: Hou, Shuyang, et al.
Pubblicazione: (2024)

TaskEval: Assessing Difficulty of Code Generation Tasks for Large Language Models
di: Tambon, Florian, et al.
Pubblicazione: (2024)

ModiGen: A Large Language Model-Based Workflow for Multi-Task Modelica Code Generation
di: Xiang, Jiahui, et al.
Pubblicazione: (2025)

Combining Large Language Models with Static Analyzers for Code Review Generation
di: Jaoua, Imen, et al.
Pubblicazione: (2025)

Evaluating Large Language Models for Code Review
di: Cihan, Umut, et al.
Pubblicazione: (2025)

Industrial-Scale Neural Network Clone Detection with Disk-Based Similarity Search
di: Ahmed, Gul Aftab, et al.
Pubblicazione: (2025)

Using Ensemble Inference to Improve Recall of Clone Detection
di: Ahmed, Gul Aftab, et al.
Pubblicazione: (2024)

Automating Patch Set Generation from Code Review Comments Using Large Language Models
di: Rahman, Tajmilur, et al.
Pubblicazione: (2024)

Automated Code Review Using Large Language Models with Symbolic Reasoning
di: Icoz, Busra, et al.
Pubblicazione: (2025)

Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation
di: Keshri, Rajat, et al.
Pubblicazione: (2025)

Code Red! On the Harmfulness of Applying Off-the-shelf Large Language Models to Programming Tasks
di: Al-Kaswan, Ali, et al.
Pubblicazione: (2025)

A Comparative Analysis of Large Language Models for Code Documentation Generation
di: Dvivedi, Shubhang Shekhar, et al.
Pubblicazione: (2023)

Personality-Guided Code Generation Using Large Language Models
di: Guo, Yaoqi, et al.
Pubblicazione: (2024)

Large Language Model Guided Self-Debugging Code Generation
di: Adnan, Muntasir, et al.
Pubblicazione: (2025)

Bugs in Large Language Models Generated Code: An Empirical Study
di: Tambon, Florian, et al.
Pubblicazione: (2024)

CodeGolf Bench: A Multi-Language Benchmark for Evaluating Concise Code Generation Capabilities of Large Language Models
di: Padwal, Vedant
Pubblicazione: (2026)

Towards Advancing Code Generation with Large Language Models: A Research Roadmap
di: Jin, Haolin, et al.
Pubblicazione: (2025)

Geo-FuB: A Method for Constructing an Operator-Function Knowledge Base for Geospatial Code Generation Tasks Using Large Language Models
di: Hou, Shuyang, et al.
Pubblicazione: (2024)

Challenges in Testing Large Language Model Based Software: A Faceted Taxonomy
di: Dobslaw, Felix, et al.
Pubblicazione: (2025)

Flow2Code: Evaluating Large Language Models for Flowchart-based Code Generation Capability
di: He, Mengliang, et al.
Pubblicazione: (2025)

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation
di: Gui, Ningxin, et al.
Pubblicazione: (2025)

Model-Driven Quantum Code Generation Using Large Language Models and Retrieval-Augmented Generation
di: Siavash, Nazanin, et al.
Pubblicazione: (2025)

CrossPL: Evaluating Large Language Models on Cross Programming Language Code Generation
di: Xiong, Zhanhang, et al.
Pubblicazione: (2025)

Large Language Models to Enhance Business Process Modeling: Past, Present, and Future Trends
di: Bettencourt, João, et al.
Pubblicazione: (2026)

COMPASS: A Multi-Dimensional Benchmark for Evaluating Code Generation in Large Language Models
di: Meaden, James, et al.
Pubblicazione: (2025)

A Deep Dive Into Large Language Model Code Generation Mistakes: What and Why?
di: Chen, QiHong, et al.
Pubblicazione: (2024)

Defective Task Descriptions in LLM-Based Code Generation: Detection and Analysis
di: Akli, Amal, et al.
Pubblicazione: (2026)

SimdBench: Benchmarking Large Language Models for SIMD-Intrinsic Code Generation
di: He, Yibo, et al.
Pubblicazione: (2025)

Beyond Autoregression: An Empirical Study of Diffusion Large Language Models for Code Generation
di: Li, Chengze, et al.
Pubblicazione: (2025)

Do Code Semantics Help? A Comprehensive Study on Execution Trace-Based Information for Code Large Language Models
di: Wang, Jian, et al.
Pubblicazione: (2025)

Reverse Engineering User Stories from Code using Large Language Models
di: Ouf, Mohamed, et al.
Pubblicazione: (2025)

Generating Energy-Efficient Code via Large-Language Models -- Where are we now?
di: Apsan, Radu, et al.
Pubblicazione: (2025)

Enhancing High-Quality Code Generation in Large Language Models with Comparative Prefix-Tuning
di: Jiang, Yuan, et al.
Pubblicazione: (2025)

Evaluating Large Language Models in Code Generation: INFINITE Methodology for Defining the Inference Index
di: Christakis, Nicholas, et al.
Pubblicazione: (2025)

An Empirical Study on Self-correcting Large Language Models for Data Science Code Generation
di: Quoc, Thai Tang, et al.
Pubblicazione: (2024)

On Assessing the Relevance of Code Reviews Authored by Generative Models
di: Heumüller, Robert, et al.
Pubblicazione: (2025)

A Study on the Improvement of Code Generation Quality Using Large Language Models Leveraging Product Documentation
di: Morimoto, Takuro, et al.
Pubblicazione: (2025)