Accelerating Verification and Software Standards Testing (AVASST) with Large Language Models (LLMs)

Abstract

The recent explosion in large language model (LLM) technology has highlighted the challenges of using public generative Artificial Intelligence (AI) tools in classified environments, especially for software analysis. Currently, software analysis falls on the shoulders of static analysis (SA) tools and manual code review, which tend to provide limited technical depth and are often time-consuming in practice. We show that LLMs can be used in unclassified environments to rapidly develop tools that accelerate software analysis in classified environments. Through LLM assistance, our work has produced several avenues for success, and preliminary experimentation has shown significant time savings (~40% ) and improved accuracy (~10%) for certain software analysis tasks.