Learning to Guarantee Type Correctness in Code Generation through Type-Guided Program Synthesis
Fuente:
arXiv
Saved in:
| Main Authors: | Huang, Zhechong, Zhang, Zhao, Ji, Ruyi, Xia, Tingxuan, Zhu, Qihao, Cao, Qinxiang, Sun, Zeyu, Zhou, Wiggin, Xiong, Yingfei |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Reinforcement Learning with Negative Tests as Completeness Signal for Formal Specification Synthesis
by: Huang, Zhechong, et al.
Published: (2026)
by: Huang, Zhechong, et al.
Published: (2026)
Lyra: A Benchmark for Turducken-Style Code Generation
by: Liang, Qingyuan, et al.
Published: (2021)
by: Liang, Qingyuan, et al.
Published: (2021)
C*: Unifying Programming and Verification in C
by: Cao, Yiyuan, et al.
Published: (2025)
by: Cao, Yiyuan, et al.
Published: (2025)
GramTrans: A Better Code Representation Approach in Code Generation
by: Zhang, Zhao, et al.
Published: (2025)
by: Zhang, Zhao, et al.
Published: (2025)
DSCodeBench: A Realistic Benchmark for Data Science Code Generation
by: Ouyang, Shuyin, et al.
Published: (2025)
by: Ouyang, Shuyin, et al.
Published: (2025)
Integrating Symbolic Execution with LLMs for Automated Generation of Program Specifications
by: Yang, Fanpeng, et al.
Published: (2025)
by: Yang, Fanpeng, et al.
Published: (2025)
HoarePrompt: Structural Reasoning About Program Correctness in Natural Language
by: Bouras, Dimitrios Stamatios, et al.
Published: (2025)
by: Bouras, Dimitrios Stamatios, et al.
Published: (2025)
Accelerating Patch Validation for Program Repair with Interception-Based Execution Scheduling
by: Xiao, Yuan-An, et al.
Published: (2023)
by: Xiao, Yuan-An, et al.
Published: (2023)
Directional Diffusion-Style Code Editing Pre-training
by: Liang, Qingyuan, et al.
Published: (2025)
by: Liang, Qingyuan, et al.
Published: (2025)
Trustworthy Software Project Generation : a Case Study with an Interactive Theorem Prover
by: Fang, Jian, et al.
Published: (2026)
by: Fang, Jian, et al.
Published: (2026)
Condor: A Code Discriminator Integrating General Semantics with Code Details
by: Liang, Qingyuan, et al.
Published: (2024)
by: Liang, Qingyuan, et al.
Published: (2024)
Co-Evolution of Types and Dependencies: Towards Repository-Level Type Inference for Python Code
by: Sun, Shuo, et al.
Published: (2025)
by: Sun, Shuo, et al.
Published: (2025)
M2CVD: Enhancing Vulnerability Semantic through Multi-Model Collaboration for Code Vulnerability Detection
by: Wang, Ziliang, et al.
Published: (2024)
by: Wang, Ziliang, et al.
Published: (2024)
SemOpt: LLM-Driven Code Optimization via Rule-Based Analysis
by: Zhao, Yuwei, et al.
Published: (2025)
by: Zhao, Yuwei, et al.
Published: (2025)
Knowledge-Enhanced Program Repair for Data Science Code
by: Ouyang, Shuyin, et al.
Published: (2025)
by: Ouyang, Shuyin, et al.
Published: (2025)
On Reasoning-Centric LLM-based Automated Theorem Proving
by: Sun, Yican, et al.
Published: (2026)
by: Sun, Yican, et al.
Published: (2026)
Line-level Semantic Structure Learning for Code Vulnerability Detection
by: Wang, Ziliang, et al.
Published: (2024)
by: Wang, Ziliang, et al.
Published: (2024)
A Learning Method for Symbolic Systems Using Large Language Models
by: Fang, Jian, et al.
Published: (2026)
by: Fang, Jian, et al.
Published: (2026)
CATCODER: Repository-Level Code Generation with Relevant Code and Type Context
by: Pan, Zhiyuan, et al.
Published: (2024)
by: Pan, Zhiyuan, et al.
Published: (2024)
Unmasking the Genuine Type Inference Capabilities of LLMs for Java Code Snippets
by: Dong, Yiwen, et al.
Published: (2025)
by: Dong, Yiwen, et al.
Published: (2025)
DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence
by: Guo, Daya, et al.
Published: (2024)
by: Guo, Daya, et al.
Published: (2024)
CodeScore-R: An Automated Robustness Metric for Assessing the FunctionalCorrectness of Code Synthesis
by: Yang, Guang, et al.
Published: (2024)
by: Yang, Guang, et al.
Published: (2024)
Type-aware LLM-based Regression Test Generation for Python Programs
by: Liu, Runlin, et al.
Published: (2025)
by: Liu, Runlin, et al.
Published: (2025)
CupCleaner: A Hybrid Data Cleaning Approach for Comment Updating
by: Liang, Qingyuan, et al.
Published: (2023)
by: Liang, Qingyuan, et al.
Published: (2023)
TypeScript Repository Indexing for Code Agent Retrieval
by: Pu, Junsong, et al.
Published: (2026)
by: Pu, Junsong, et al.
Published: (2026)
NovaQ: Improving Quantum Program Testing through Diversity-Guided Test Case Generation
by: Jin, Tiancheng, et al.
Published: (2025)
by: Jin, Tiancheng, et al.
Published: (2025)
LLM-based Vulnerability Detection at Project Scale: An Empirical Study
by: Li, Fengjie, et al.
Published: (2026)
by: Li, Fengjie, et al.
Published: (2026)
Mining Type Constructs Using Patterns in AI-Generated Code
by: Lee, Imgyeong, et al.
Published: (2026)
by: Lee, Imgyeong, et al.
Published: (2026)
A Survey on Feedback Types in Automated Programming Assessment Systems
by: Frankford, Eduard, et al.
Published: (2025)
by: Frankford, Eduard, et al.
Published: (2025)
CC2Vec: Combining Typed Tokens with Contrastive Learning for Effective Code Clone Detection
by: Dou, Shihan, et al.
Published: (2024)
by: Dou, Shihan, et al.
Published: (2024)
PredicateFix: Repairing Static Analysis Alerts with Bridging Predicates
by: Xiao, Yuan-An, et al.
Published: (2025)
by: Xiao, Yuan-An, et al.
Published: (2025)
Guided Debugging of Auto-Translated Code Using Differential Testing
by: Wu, Shengnan, et al.
Published: (2025)
by: Wu, Shengnan, et al.
Published: (2025)
Contextualized Code Pretraining for Code Generation
by: Liu, Chen, et al.
Published: (2026)
by: Liu, Chen, et al.
Published: (2026)
What Types of Code Review Comments Do Developers Most Frequently Resolve?
by: Goldman, Saul, et al.
Published: (2025)
by: Goldman, Saul, et al.
Published: (2025)
Knowledge-Guided Multi-Agent Framework for Application-Level Software Code Generation
by: Xiong, Qian, et al.
Published: (2025)
by: Xiong, Qian, et al.
Published: (2025)
Correctness-Guaranteed Code Generation via Constrained Decoding
by: Li, Lingxiao, et al.
Published: (2025)
by: Li, Lingxiao, et al.
Published: (2025)
AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators
by: Chou, Jason, et al.
Published: (2025)
by: Chou, Jason, et al.
Published: (2025)
Across Programming Language Silos: A Study on Cross-Lingual Retrieval-augmented Code Generation
by: Zhu, Qiming, et al.
Published: (2025)
by: Zhu, Qiming, et al.
Published: (2025)
GRACE: Graph-Guided Repository-Aware Code Completion through Hierarchical Code Fusion
by: Wang, Xingliang, et al.
Published: (2025)
by: Wang, Xingliang, et al.
Published: (2025)
To Type or Not to Type? A Systematic Comparison of the Software Quality of JavaScript and TypeScript Applications on GitHub
by: Bogner, Justus, et al.
Published: (2022)
by: Bogner, Justus, et al.
Published: (2022)
Similar Items
-
Reinforcement Learning with Negative Tests as Completeness Signal for Formal Specification Synthesis
by: Huang, Zhechong, et al.
Published: (2026) -
Lyra: A Benchmark for Turducken-Style Code Generation
by: Liang, Qingyuan, et al.
Published: (2021) -
C*: Unifying Programming and Verification in C
by: Cao, Yiyuan, et al.
Published: (2025) -
GramTrans: A Better Code Representation Approach in Code Generation
by: Zhang, Zhao, et al.
Published: (2025) -
DSCodeBench: A Realistic Benchmark for Data Science Code Generation
by: Ouyang, Shuyin, et al.
Published: (2025)