4 papers
Leveraging Large Language Models to Obscure Code Stylometry: A Comparative Study of GPT-3.5 and GPT-4
Saman Pordanesh, Benjamin Tan
In the rapidly evolving field of software development, code stylometry analyzing unique stylistic signatures of programmers plays a crit-ical role in authorship attribution and cyb…
PCB-QA: Evaluating LLMs over the First Printed Circuit Board Design Question-Answer Dataset
Sahana Srinivasan, Benjamin Tan, Benjamin Turnbull +1
Large Language Models (LLMs) have demonstrated capabilities in electronic design automation (EDA) for integrated circuits. However, their applications in printed circuit board (PCB…
Towards LLM-based Root Cause Analysis of Hardware Design Failures
Siyu Qiu, Muzhi Wang, Raheel Afsharmazayejani +3
With advances in large language models (LLMs), new opportunities have emerged to develop tools that support the digital hardware design process. In this work, we explore how LLMs c…
LASHED: LLMs And Static Hardware Analysis for Early Detection of RTL Bugs
Baleegh Ahmad, Hammond Pearce, Ramesh Karri +1
While static analysis is useful in detecting early-stage hardware security bugs, its efficacy is limited because it requires information to form checks and is often unable to expla…