LLM Agent-Assisted Reverse Engineering with Quantitative Readability Metrics
Researchers have developed a new framework called Quantitative Readability Score (QRS) to improve the readability of decompiled code using LLM agents. The QRS framework combines structural similarity with metrics for lexical surprisal, structural simplicity, and idiomatic quality. This approach allows LLM agents to make targeted readability improvements without compromising the correctness of the decompiled code. AI
IMPACT Enhances code analysis tools by improving the clarity of decompiled code, potentially speeding up reverse engineering tasks.