Copertina

A Survey of using Large Language Models for Generating Infrastructure as Code

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Srivatsa, Kalahasti Ganesh, Mukhopadhyay, Sabyasachi, Katrapati, Ganesh, Shrivastava, Manish
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Software Engineering Computation and Language
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Can Constructions "SCAN" Compositionality ?
di: Katrapati, Ganesh, et al.
Pubblicazione: (2025)

A Code Comprehension Benchmark for Large Language Models for Code
di: Havare, Jayant, et al.
Pubblicazione: (2025)

A Survey on Large Language Models for Code Generation
di: Jiang, Juyong, et al.
Pubblicazione: (2024)

kRAIG: A Natural Language-Driven Agent for Automated DataOps Pipeline Generation
di: Siva, Rohan, et al.
Pubblicazione: (2026)

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators
di: Chou, Jason, et al.
Pubblicazione: (2025)

Enhanced Automated Code Vulnerability Repair using Large Language Models
di: de-Fitero-Dominguez, David, et al.
Pubblicazione: (2024)

Is Your AI-Generated Code Really Safe? Evaluating Large Language Models on Secure Code Generation with CodeSecEval
di: Wang, Jiexin, et al.
Pubblicazione: (2024)

Leveraging Print Debugging to Improve Code Generation in Large Language Models
di: Hu, Xueyu, et al.
Pubblicazione: (2024)

SV-TrustEval-C: Evaluating Structure and Semantic Reasoning in Large Language Models for Source Code Vulnerability Analysis
di: Li, Yansong, et al.
Pubblicazione: (2025)

Mercury: A Code Efficiency Benchmark for Code Large Language Models
di: Du, Mingzhe, et al.
Pubblicazione: (2024)

What's Wrong with Your Code Generated by Large Language Models? An Extensive Study
di: Dou, Shihan, et al.
Pubblicazione: (2024)

A Survey of AIOps in the Era of Large Language Models
di: Zhang, Lingzhe, et al.
Pubblicazione: (2025)

Enhancing Code LLMs with Reinforcement Learning in Code Generation: A Survey
di: Wang, Junqiao, et al.
Pubblicazione: (2024)

Calibration of Large Language Models on Code Summarization
di: Virk, Yuvraj, et al.
Pubblicazione: (2024)

Semantic Source Code Segmentation using Small and Large Language Models
di: Dahou, Abdelhalim, et al.
Pubblicazione: (2025)

Bridging Code Graphs and Large Language Models for Better Code Understanding
di: Chen, Zeqi, et al.
Pubblicazione: (2025)

CodeJudge: Evaluating Code Generation with Large Language Models
di: Tong, Weixi, et al.
Pubblicazione: (2024)

CodeMirage: Hallucinations in Code Generated by Large Language Models
di: Agarwal, Vibhor, et al.
Pubblicazione: (2024)

CodeReviewQA: The Code Review Comprehension Assessment for Large Language Models
di: Lin, Hong Yi, et al.
Pubblicazione: (2025)

Novel Preprocessing Technique for Data Embedding in Engineering Code Generation Using Large Language Model
di: Lin, Yu-Chen, et al.
Pubblicazione: (2023)

CodeJudge-Eval: Can Large Language Models be Good Judges in Code Understanding?
di: Zhao, Yuwei, et al.
Pubblicazione: (2024)

HumanEval Pro and MBPP Pro: Evaluating Large Language Models on Self-invoking Code Generation
di: Yu, Zhaojian, et al.
Pubblicazione: (2024)

Using Large Language Models for Student-Code Guided Test Case Generation in Computer Science Education
di: Kumar, Nischal Ashok, et al.
Pubblicazione: (2024)

EffiCoder: Enhancing Code Generation in Large Language Models through Efficiency-Aware Fine-tuning
di: Huang, Dong, et al.
Pubblicazione: (2024)

ArchCode: Incorporating Software Requirements in Code Generation with Large Language Models
di: Han, Hojae, et al.
Pubblicazione: (2024)

InstructCoder: Instruction Tuning Large Language Models for Code Editing
di: Li, Kaixin, et al.
Pubblicazione: (2023)

GLLM: Self-Corrective G-Code Generation using Large Language Models with User Feedback
di: Abdelaal, Mohamed, et al.
Pubblicazione: (2025)

Evaluating the Generalization Capabilities of Large Language Models on Code Reasoning
di: Yang, Rem, et al.
Pubblicazione: (2025)

Retrieval-Augmented Code Generation: A Survey with Focus on Repository-Level Approaches
di: Tao, Yicheng, et al.
Pubblicazione: (2025)

From Code Foundation Models to Agents and Applications: A Comprehensive Survey and Practical Guide to Code Intelligence
di: Yang, Jian, et al.
Pubblicazione: (2025)

ScaleBox: Enabling High-Fidelity and Scalable Code Verification for Large Language Models
di: Zheng, Jiasheng, et al.
Pubblicazione: (2026)

Exploring Data-Efficient Adaptation of Large Language Models for Code Generation
di: Jiang, Xue, et al.
Pubblicazione: (2024)

Self-Explained Keywords Empower Large Language Models for Code Generation
di: Fan, Lishui, et al.
Pubblicazione: (2024)

CodeOCR: On the Effectiveness of Vision Language Models in Code Understanding
di: Shi, Yuling, et al.
Pubblicazione: (2026)

VHDL-Eval: A Framework for Evaluating Large Language Models in VHDL Code Generation
di: Vijayaraghavan, Prashanth, et al.
Pubblicazione: (2024)

Improving Small Language Models for Code Generation with Reinforcement Learning from Verification Feedback
di: Skopin, Egor, et al.
Pubblicazione: (2026)

Beyond Correctness: Benchmarking Multi-dimensional Code Generation for Large Language Models
di: Zheng, Jiasheng, et al.
Pubblicazione: (2024)

Generating and Evaluating Sustainable Procurement Criteria for the Swiss Public Sector using In-Context Prompting with Large Language Models
di: Gao, Yingqiang, et al.
Pubblicazione: (2026)

LongCodeZip: Compress Long Context for Code Language Models
di: Shi, Yuling, et al.
Pubblicazione: (2025)

R2C2-Coder: Enhancing and Benchmarking Real-world Repository-level Code Completion Abilities of Code Large Language Models
di: Deng, Ken, et al.
Pubblicazione: (2024)