Generative AI Augmented Induction-based Formal Verification

Fuente: arXiv
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Autores principales: Kumar, Aman, Gadde, Deepak Narayan
Formato: Preprint
Publicado: 2024
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author Kumar, Aman
Gadde, Deepak Narayan
author_facet Kumar, Aman
Gadde, Deepak Narayan
contents Generative Artificial Intelligence (GenAI) has demonstrated its capabilities in the present world that reduce human effort significantly. It utilizes deep learning techniques to create original and realistic content in terms of text, images, code, music, and video. Researchers have also shown the capabilities of modern Large Language Models (LLMs) used by GenAI models that can be used to aid hardware development. Formal verification is a mathematical-based proof method used to exhaustively verify the correctness of a design. In this paper, we demonstrate how GenAI can be used in induction-based formal verification to increase the verification throughput.
format Preprint
id arxiv_https___arxiv_org_abs_2407_18965
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Generative AI Augmented Induction-based Formal Verification
Kumar, Aman
Gadde, Deepak Narayan
Artificial Intelligence
Generative Artificial Intelligence (GenAI) has demonstrated its capabilities in the present world that reduce human effort significantly. It utilizes deep learning techniques to create original and realistic content in terms of text, images, code, music, and video. Researchers have also shown the capabilities of modern Large Language Models (LLMs) used by GenAI models that can be used to aid hardware development. Formal verification is a mathematical-based proof method used to exhaustively verify the correctness of a design. In this paper, we demonstrate how GenAI can be used in induction-based formal verification to increase the verification throughput.
title Generative AI Augmented Induction-based Formal Verification
topic Artificial Intelligence
url https://arxiv.org/abs/2407.18965