Assumption Mining
Assumption Mining is a formal method in assertion-based verification that identifies and extracts implicit system-level assumptions from hardware or software designs to refine verification scopes and enhance property generation.
5
Publications
224
Citations
15
Authors
7
Institutions
Publications per year
2017–2026
1
Parents
5
Mining assumptions for synthesis
Wenchao Li, Lili Dworkin, Sanjit A. Seshia · 2011 · 102 citations
Mining assumptions for software components using machine learning
Khouloud Gaaloul, Claudio Menghi, Shiva Nejati et al. · 2020 · 17 citations · Full text
Software Assumptions Lead to Preventable Errors
Andy Steingruebl, Gunnar Peterson · IEEE Security & Privacy · 2009 · 16 citations
1–5 of 5
15
2
h-index
1
h-index
Activated Research Company (United States), United States
1 publications · 16 citations
1
h-index
1
h-index
1
h-index
1–5 of 15
7
University of California, Berkeley
Berkeley, United States
2 h-index
5 publications
270 citations
Cadence Design Systems (United States)
San Jose, United States
1 h-index
3 publications
201 citations

University of Ottawa
Ottawa, Canada
1 h-index
2 publications
34 citations
Berkeley College
New York, United States
1 h-index
2 publications
204 citations
University of Luxembourg
Luxembourg, Luxembourg
1 h-index
4 publications
68 citations
PayPal (United States)
San Jose, United States
1 h-index
1 publications
16 citations

Haverford College
Haverford, United States
1 h-index
1 publications
102 citations
1–7 of 7
1 publications · 16 citations
1
h-index
1 publications · 67 citations
1
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1–2