You Don't Need Public Tests to Generate Correct Code
Fuente:
arXiv
Saved in:
| Main Authors: | Silva, Kaushitha, Perera, Srinath |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
BACE: LLM-based Code Generation through Bayesian Anchored Co-Evolution of Code and Test Populations
by: Silva, Kaushitha, et al.
Published: (2026)
by: Silva, Kaushitha, et al.
Published: (2026)
LLMLOOP: Improving LLM-Generated Code and Tests through Automated Iterative Feedback Loops
by: Ravi, Ravin, et al.
Published: (2026)
by: Ravi, Ravin, et al.
Published: (2026)
ATLAS: A Layered Constraint-Guided Framework for Structured Artifact Generation in LLM-Assisted MDE
by: Ma, Tong, et al.
Published: (2025)
by: Ma, Tong, et al.
Published: (2025)
Code Generation for Machine Learning using Model-Driven Engineering and SysML
by: Raedler, Simon, et al.
Published: (2023)
by: Raedler, Simon, et al.
Published: (2023)
Multicalibration for LLM-based Code Generation
by: Campos, Viola, et al.
Published: (2025)
by: Campos, Viola, et al.
Published: (2025)
Validating Solidity Code Defects using Symbolic and Concrete Execution powered by Large Language Models
by: Susan, Ştefan-Claudiu, et al.
Published: (2025)
by: Susan, Ştefan-Claudiu, et al.
Published: (2025)
Test-driven Software Experimentation with LASSO: an LLM Prompt Benchmarking Example
by: Kessel, Marcus
Published: (2024)
by: Kessel, Marcus
Published: (2024)
LLM-Assisted Translation of Legacy FORTRAN Codes to C++: A Cross-Platform Study
by: Ranasinghe, Nishath Rajiv, et al.
Published: (2025)
by: Ranasinghe, Nishath Rajiv, et al.
Published: (2025)
Machine Learning-Based Detection of MCP Attacks
by: Mattsson, Tobias, et al.
Published: (2026)
by: Mattsson, Tobias, et al.
Published: (2026)
Synergy of Large Language Model and Model Driven Engineering for Automated Development of Centralized Vehicular Systems
by: Petrovic, Nenad, et al.
Published: (2024)
by: Petrovic, Nenad, et al.
Published: (2024)
Towards Single-System Illusion in Software-Defined Vehicles -- Automated, AI-Powered Workflow
by: Lebioda, Krzysztof, et al.
Published: (2024)
by: Lebioda, Krzysztof, et al.
Published: (2024)
N-Version Assessment and Enhancement of Generative AI
by: Kessel, Marcus, et al.
Published: (2024)
by: Kessel, Marcus, et al.
Published: (2024)
The Specification as Quality Gate: Three Hypotheses on AI-Assisted Code Review
by: Zietsman, Christo
Published: (2026)
by: Zietsman, Christo
Published: (2026)
Morescient GAI for Software Engineering (Extended Version)
by: Kessel, Marcus, et al.
Published: (2024)
by: Kessel, Marcus, et al.
Published: (2024)
Inside the Scaffold: A Source-Code Taxonomy of Coding Agent Architectures
by: Rombaut, Benjamin
Published: (2026)
by: Rombaut, Benjamin
Published: (2026)
AIRA: AI-Induced Risk Audit: A Structured Inspection Framework for AI-Generated Code
by: Parris, William M.
Published: (2026)
by: Parris, William M.
Published: (2026)
Towards Observation Lakehouses: Living, Interactive Archives of Software Behavior
by: Kessel, Marcus
Published: (2025)
by: Kessel, Marcus
Published: (2025)
A Prompt Learning Framework for Source Code Summarization
by: Xu, Tingting, et al.
Published: (2023)
by: Xu, Tingting, et al.
Published: (2023)
AI for software engineering: from probable to provable
by: Meyer, Bertrand
Published: (2025)
by: Meyer, Bertrand
Published: (2025)
Cryptographic Registry Provenance: Structural Defense Against Dependency Confusion in AI Package Ecosystems
by: McCann, Alan L.
Published: (2026)
by: McCann, Alan L.
Published: (2026)
Uncovering Bugs in Formal Explainers: A Case Study with PyXAI
by: Huang, Xuanxiang, et al.
Published: (2025)
by: Huang, Xuanxiang, et al.
Published: (2025)
Adaptive and AI-Augmented Security Testing: A Systematic Survey of Program Analysis, Feedback-Driven Testing, and Hybrid Learning-Based Approaches
by: Wienczkowski, Michael
Published: (2026)
by: Wienczkowski, Michael
Published: (2026)
The Two Boundaries: Why Behavioral AI Governance Fails Structurally
by: McCann, Alan L.
Published: (2026)
by: McCann, Alan L.
Published: (2026)
LLM4PLC: Harnessing Large Language Models for Verifiable Programming of PLCs in Industrial Control Systems
by: Fakih, Mohamad, et al.
Published: (2024)
by: Fakih, Mohamad, et al.
Published: (2024)
Monitoring Agentic Systems Before They're Reliable
by: Boston, Marisa Ferrara, et al.
Published: (2026)
by: Boston, Marisa Ferrara, et al.
Published: (2026)
Structural Quality Gaps in Practitioner AI Governance Prompts: An Empirical Study Using a Five-Principle Evaluation Framework
by: Zietsman, Christo
Published: (2026)
by: Zietsman, Christo
Published: (2026)
Towards a Probabilistic Framework for Analyzing and Improving LLM-Enabled Software
by: Baldonado, Juan Manuel, et al.
Published: (2025)
by: Baldonado, Juan Manuel, et al.
Published: (2025)
Automated structural testing of LLM-based agents: methods, framework, and case studies
by: Kohl, Jens, et al.
Published: (2026)
by: Kohl, Jens, et al.
Published: (2026)
A History Equivalence Algorithm for Dynamic Process Migration
by: Bakshi, Gargi, et al.
Published: (2024)
by: Bakshi, Gargi, et al.
Published: (2024)
Iterative Audit Convergence in LLM-Managed Multi-Agent Systems: A Case Study in Prompt Engineering Quality Assurance
by: Calboreanu, Elias
Published: (2026)
by: Calboreanu, Elias
Published: (2026)
Rango: Adaptive Retrieval-Augmented Proving for Automated Software Verification
by: Thompson, Kyle, et al.
Published: (2024)
by: Thompson, Kyle, et al.
Published: (2024)
A Pattern Language for Resilient Visual Agents
by: Gidey, Habtom Kahsay, et al.
Published: (2026)
by: Gidey, Habtom Kahsay, et al.
Published: (2026)
Engineering Systems for Data Analysis Using Interactive Structured Inductive Programming
by: Surana, Shraddha, et al.
Published: (2025)
by: Surana, Shraddha, et al.
Published: (2025)
From Scientific Texts to Verifiable Code: Automating the Process with Transformers
by: Wang, Changjie, et al.
Published: (2025)
by: Wang, Changjie, et al.
Published: (2025)
EvoGraph: Hybrid Directed Graph Evolution toward Software 3.0
by: Costa, Igor, et al.
Published: (2025)
by: Costa, Igor, et al.
Published: (2025)
CodeCompass: Navigating the Navigation Paradox in Agentic Code Intelligence
by: Paipuru, Tarakanath
Published: (2026)
by: Paipuru, Tarakanath
Published: (2026)
TerraFormer: Automated Infrastructure-as-Code with LLMs Fine-Tuned via Policy-Guided Verifier Feedback
by: Jana, Prithwish, et al.
Published: (2026)
by: Jana, Prithwish, et al.
Published: (2026)
Automated Deep Learning Optimization via DSL-Based Source Code Transformation
by: Wang, Ruixin, et al.
Published: (2024)
by: Wang, Ruixin, et al.
Published: (2024)
Compiled AI: Deterministic Code Generation for LLM-Based Workflow Automation
by: Trooskens, Geert, et al.
Published: (2026)
by: Trooskens, Geert, et al.
Published: (2026)
DEFault++: Automated Fault Detection, Categorization, and Diagnosis for Transformer Architectures
by: Jahan, Sigma, et al.
Published: (2026)
by: Jahan, Sigma, et al.
Published: (2026)
Similar Items
-
BACE: LLM-based Code Generation through Bayesian Anchored Co-Evolution of Code and Test Populations
by: Silva, Kaushitha, et al.
Published: (2026) -
LLMLOOP: Improving LLM-Generated Code and Tests through Automated Iterative Feedback Loops
by: Ravi, Ravin, et al.
Published: (2026) -
ATLAS: A Layered Constraint-Guided Framework for Structured Artifact Generation in LLM-Assisted MDE
by: Ma, Tong, et al.
Published: (2025) -
Code Generation for Machine Learning using Model-Driven Engineering and SysML
by: Raedler, Simon, et al.
Published: (2023) -
Multicalibration for LLM-based Code Generation
by: Campos, Viola, et al.
Published: (2025)