LLM Generated Code

Large language models (LLMs) are increasingly used to generate code, aiming to automate software development and improve programmer productivity. Current research focuses on mitigating the significant security vulnerabilities and functional inaccuracies frequently found in LLM-generated code, exploring techniques like improved prompting strategies, fine-tuning with synthetic secure code datasets, and post-generation verification methods. This field is crucial because the widespread adoption of LLM-generated code necessitates robust methods for ensuring code quality, security, and compliance, impacting software development practices and potentially reshaping software engineering workflows.