Image de couverture de livre

FRANC: A Lightweight Framework for High-Quality Code Generation

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Siddiq, Mohammed Latif, Casey, Beatrice, Santos, Joanna C. S.
Format:	Preprint
Publié:	2023
Sujets:	Software Engineering Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

The Fault in our Stars: Quality Assessment of Code Generation Benchmarks
par: Siddiq, Mohammed Latif, et autres
Publié: (2024)

Large Language Models for Software Engineering: A Reproducibility Crisis
par: Siddiq, Mohammed Latif, et autres
Publié: (2025)

An Empirical Study on Remote Code Execution in Machine Learning Model Hosting Ecosystems
par: Siddiq, Mohammed Latif, et autres
Publié: (2026)

Using Large Language Models to Generate JUnit Tests: An Empirical Study
par: Siddiq, Mohammed Latif, et autres
Publié: (2023)

SALLM: Security Assessment of Generated Code
par: Siddiq, Mohammed Latif, et autres
Publié: (2023)

Assessing the Software Security Comprehension of Large Language Models
par: Siddiq, Mohammed Latif, et autres
Publié: (2025)

Security in the Age of AI Teammates: An Empirical Study of Agentic Pull Requests on GitHub
par: Siddiq, Mohammed Latif, et autres
Publié: (2026)

A Large-Scale Exploit Instrumentation Study of AI/ML Supply Chain Attacks in Hugging Face Models
par: Casey, Beatrice, et autres
Publié: (2024)

Security and Quality in LLM-Generated Code: A Multi-Language, Multi-Model Analysis
par: Kharma, Mohammed, et autres
Publié: (2025)

Assessing the Quality and Security of AI-Generated Code: A Quantitative Analysis
par: Sabra, Abbas, et autres
Publié: (2025)

Enhancing Code Quality with Generative AI: Boosting Developer Warning Compliance
par: Chang, Hansen, et autres
Publié: (2025)

JARVIS: A Multi-Agent Code Assistant for High-Quality EDA Script Generation
par: Pasandi, Ghasem, et autres
Publié: (2025)

Reinforcement Learning from Automatic Feedback for High-Quality Unit Test Generation
par: Steenhoek, Benjamin, et autres
Publié: (2023)

Reinforcement Learning from Automatic Feedback for High-Quality Unit Test Generation
par: Steenhoek, Benjamin, et autres
Publié: (2024)

A Configuration-First Framework for Reproducible, Low-Code Localization
par: Strnad, Tim, et autres
Publié: (2025)

SemRep: Generative Code Representation Learning with Code Transformations
par: Li, Weichen, et autres
Publié: (2026)

Think Anywhere in Code Generation
par: Jiang, Xue, et autres
Publié: (2026)

Code Roulette: How Prompt Variability Affects LLM Code Generation
par: Paleyes, Andrei, et autres
Publié: (2025)

An Empirical Study of Safetensors' Usage Trends and Developers' Perceptions
par: Casey, Beatrice, et autres
Publié: (2025)

Model Cascading for Code: A Cascaded Black-Box Multi-Model Framework for Cost-Efficient Code Completion with Self-Testing
par: Chen, Boyuan, et autres
Publié: (2024)

CodeIF: Benchmarking the Instruction-Following Capabilities of Large Language Models for Code Generation
par: Yan, Kaiwen, et autres
Publié: (2025)

LLM Performance for Code Generation on Noisy Tasks
par: Sendyka, Radzim, et autres
Publié: (2025)

OSS-Bench: Benchmark Generator for Coding LLMs
par: Jiang, Yuancheng, et autres
Publié: (2025)

AICD Bench: A Challenging Benchmark for AI-Generated Code Detection
par: Orel, Daniil, et autres
Publié: (2026)

Code Less, Align More: Efficient LLM Fine-tuning for Code Generation with Data Pruning
par: Tsai, Yun-Da, et autres
Publié: (2024)

StructCoder: Structure-Aware Transformer for Code Generation
par: Tipirneni, Sindhu, et autres
Publié: (2022)

Leveraging Reviewer Experience in Code Review Comment Generation
par: Lin, Hong Yi, et autres
Publié: (2024)

SQAPlanner: Generating Data-Informed Software Quality Improvement Plans
par: Rajapaksha, Dilini, et autres
Publié: (2021)

Domain-Adaptable Reinforcement Learning for Code Generation with Dense Rewards
par: Jolfaei, Erfan Aghadavoodi, et autres
Publié: (2026)

Design-Specification Tiling for ICL-based CAD Code Generation
par: Du, Yali, et autres
Publié: (2026)

Context-Augmented Code Generation Using Programming Knowledge Graphs
par: Seddik, Shahd, et autres
Publié: (2026)

Leveraging Reward Models for Guiding Code Review Comment Generation
par: Sghaier, Oussama Ben, et autres
Publié: (2025)

Ensuring Functional Correctness of Large Code Models with Selective Generation
par: Jeong, Jaewoo, et autres
Publié: (2025)

You Only Train Once: A Flexible Training Framework for Code Vulnerability Detection Driven by Vul-Vector
par: Tian, Bowen, et autres
Publié: (2025)

Large Language Models for Code Generation: A Comprehensive Survey of Challenges, Techniques, Evaluation, and Applications
par: Huynh, Nam, et autres
Publié: (2025)

A Survey on LLM-based Code Generation for Low-Resource and Domain-Specific Programming Languages
par: Joel, Sathvik, et autres
Publié: (2024)

GitChameleon: Unmasking the Version-Switching Capabilities of Code Generation Models
par: Islah, Nizar, et autres
Publié: (2024)

How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark
par: Qiu, Ruizhong, et autres
Publié: (2024)

A Comprehensive Framework for Evaluating API-oriented Code Generation in Large Language Models
par: Wu, Yixi, et autres
Publié: (2024)

Code-Aware Prompting: A study of Coverage Guided Test Generation in Regression Setting using LLM
par: Ryan, Gabriel, et autres
Publié: (2024)