Bridging Human Language and Command Line
Enhancing LLM-based translation from natural language to Bash
This research introduces a new framework for evaluating and improving how Large Language Models translate everyday language into Bash commands, addressing critical security and usability challenges.
- Created a manually verified dataset of 300 natural language to Bash command pairs
- Developed a more accurate evaluation methodology to measure functional equivalence of Bash commands
- Found LLMs achieve up to 80% accuracy in command translation tasks
- Proposed a hybrid approach combining LLM reasoning with syntax checking for improved performance
The security implications are significant: reliable natural language interfaces for command line operations reduce the risk of syntax errors and security vulnerabilities while making system administration more accessible to non-experts.