RFCScope: Detecting Logical Ambiguities in Internet Protocol Specifications
Published in ASE, 2025
This paper addresses the challenge of generating code that is not only functional but also safe and correct. We propose a framework that integrates formal verification techniques with large language models, ensuring that generated code adheres to formal specifications and program semantics.
Key Contributions
- Novel integration of LLMs with formal verification
- Automated safety checking for generated code
- Experimental evaluation on multiple benchmarks
Results
Our approach significantly improves the safety and correctness of LLM-generated code while maintaining high functionality.
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