Imagen de Portada

Assessing the Quality and Security of AI-Generated Code: A Quantitative Analysis

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Sabra, Abbas, Schmitt, Olivier, Tyler, Joseph
Formato:	Preprint
Publicado:	2025
Materias:	Software Engineering Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Security and Quality in LLM-Generated Code: A Multi-Language, Multi-Model Analysis
por: Kharma, Mohammed, et al.
Publicado: (2025)

Enhancing Code Quality with Generative AI: Boosting Developer Warning Compliance
por: Chang, Hansen, et al.
Publicado: (2025)

A Theoretical Analysis of Test-Driven Code Generation
por: Menet, Nicolas, et al.
Publicado: (2026)

FRANC: A Lightweight Framework for High-Quality Code Generation
por: Siddiq, Mohammed Latif, et al.
Publicado: (2023)

The Fault in our Stars: Quality Assessment of Code Generation Benchmarks
por: Siddiq, Mohammed Latif, et al.
Publicado: (2024)

AICD Bench: A Challenging Benchmark for AI-Generated Code Detection
por: Orel, Daniil, et al.
Publicado: (2026)

Rethinking the Evaluation of Secure Code Generation
por: Dai, Shih-Chieh, et al.
Publicado: (2025)

PromSec: Prompt Optimization for Secure Generation of Functional Source Code with Large Language Models (LLMs)
por: Nazzal, Mahmoud, et al.
Publicado: (2024)

RESCUE: Retrieval Augmented Secure Code Generation
por: Shi, Jiahao, et al.
Publicado: (2025)

Security Degradation in Iterative AI Code Generation -- A Systematic Analysis of the Paradox
por: Shukla, Shivani, et al.
Publicado: (2025)

Where Do LLMs Still Struggle? An In-Depth Analysis of Code Generation Benchmarks
por: Sharifloo, Amir Molzam, et al.
Publicado: (2025)

Optimizing AI-Assisted Code Generation
por: Torka, Simon, et al.
Publicado: (2024)

SemRep: Generative Code Representation Learning with Code Transformations
por: Li, Weichen, et al.
Publicado: (2026)

Think Anywhere in Code Generation
por: Jiang, Xue, et al.
Publicado: (2026)

CWEval: Outcome-driven Evaluation on Functionality and Security of LLM Code Generation
por: Peng, Jinjun, et al.
Publicado: (2025)

Full Line Code Completion: Bringing AI to Desktop
por: Semenkin, Anton, et al.
Publicado: (2024)

Code Roulette: How Prompt Variability Affects LLM Code Generation
por: Paleyes, Andrei, et al.
Publicado: (2025)

Leveraging Code Cohesion Analysis to Identify Source Code Supply Chain Attacks
por: Reuben, Maor, et al.
Publicado: (2025)

Unintentional Security Flaws in Code: Automated Defense via Root Cause Analysis
por: Islam, Nafis Tanveer, et al.
Publicado: (2024)

CodeIF: Benchmarking the Instruction-Following Capabilities of Large Language Models for Code Generation
por: Yan, Kaiwen, et al.
Publicado: (2025)

Can LLMs Find Bugs in Code? An Evaluation from Beginner Errors to Security Vulnerabilities in Python and C++
por: Mhatre, Akshay, et al.
Publicado: (2025)

JARVIS: A Multi-Agent Code Assistant for High-Quality EDA Script Generation
por: Pasandi, Ghasem, et al.
Publicado: (2025)

Constrained Decoding for Secure Code Generation
por: Fu, Yanjun, et al.
Publicado: (2024)

Instruction Tuning for Secure Code Generation
por: He, Jingxuan, et al.
Publicado: (2024)

LLM Performance for Code Generation on Noisy Tasks
por: Sendyka, Radzim, et al.
Publicado: (2025)

OSS-Bench: Benchmark Generator for Coding LLMs
por: Jiang, Yuancheng, et al.
Publicado: (2025)

Assessing the Software Security Comprehension of Large Language Models
por: Siddiq, Mohammed Latif, et al.
Publicado: (2025)

Code Less, Align More: Efficient LLM Fine-tuning for Code Generation with Data Pruning
por: Tsai, Yun-Da, et al.
Publicado: (2024)

StructCoder: Structure-Aware Transformer for Code Generation
por: Tipirneni, Sindhu, et al.
Publicado: (2022)

Leveraging Reviewer Experience in Code Review Comment Generation
por: Lin, Hong Yi, et al.
Publicado: (2024)

DeputyDev -- AI Powered Developer Assistant: Breaking the Code Review Logjam through Contextual AI to Boost Developer Productivity
por: Khare, Vishal, et al.
Publicado: (2025)

Grounded AI for Code Review: Resource-Efficient Large-Model Serving in Enterprise Pipelines
por: Mandal, Sayan, et al.
Publicado: (2025)

SQAPlanner: Generating Data-Informed Software Quality Improvement Plans
por: Rajapaksha, Dilini, et al.
Publicado: (2021)

Leveraging Reward Models for Guiding Code Review Comment Generation
por: Sghaier, Oussama Ben, et al.
Publicado: (2025)

Ensuring Functional Correctness of Large Code Models with Selective Generation
por: Jeong, Jaewoo, et al.
Publicado: (2025)

Domain-Adaptable Reinforcement Learning for Code Generation with Dense Rewards
por: Jolfaei, Erfan Aghadavoodi, et al.
Publicado: (2026)

Design-Specification Tiling for ICL-based CAD Code Generation
por: Du, Yali, et al.
Publicado: (2026)

Context-Augmented Code Generation Using Programming Knowledge Graphs
por: Seddik, Shahd, et al.
Publicado: (2026)

Prompting Techniques for Secure Code Generation: A Systematic Investigation
por: Tony, Catherine, et al.
Publicado: (2024)

Large Language Models for Code Generation: A Comprehensive Survey of Challenges, Techniques, Evaluation, and Applications
por: Huynh, Nam, et al.
Publicado: (2025)