Automatic Assertion Mining in Assertion-Based Verification: Techniques, Challenges, and Future Directions
The work
| Authors | Iman, Mohammad Reza Heidari; Di Natale, Giorgio; Morin-Allory, Katell |
|---|---|
| Editors | |
| Type | misc |
| Year | 2026 |
| Also known as | anon2026automatic |
| Citekey | iman2026automatic |
Where it appeared
| Publisher | arXiv |
|---|
Identifiers
| arXiv | 2601.02248 from its doi |
|---|---|
| DOI | 10.48550/arxiv.2601.02248 |
From datacite.
Abstract
Functional verification increasingly relies on Assertion-Based Verification (ABV), which has become a key approach for verifying hardware designs due to its efficiency and effectiveness. Central to ABV are automatic assertion miners, which apply different techniques to generate assertions automatically. This paper reviews the most recent, advanced, and widely adopted assertion miners, offering a comparative analysis of their methodologies. The goal is to provide researchers and verification practitioners with insights into the capabilities and limitations of existing miners. By identifying their shortcomings, this work also points toward directions for developing more powerful and advanced assertion miners in the future.
A copy is held
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How it got here
| How it got here | agent via datacite |
|---|---|
| Added | 2026-10-22 17:23 UTC |
| Approved by | a person 2026-10-22 23:07 UTC |
Cite it as
@misc{iman2026automatic,
title = {Automatic Assertion Mining in Assertion-Based Verification: Techniques, Challenges, and Future Directions},
author = {Iman, Mohammad Reza Heidari and Di Natale, Giorgio and Morin-Allory, Katell},
year = {2026},
publisher = {arXiv},
doi = {10.48550/arxiv.2601.02248},
}
This record lives at https://refs.drheap.org/iman2026automatic/ and will keep
doing so. It used to be called anon2026automatic, and those addresses still resolve to this one.