Abstract
Assume-guarantee reasoning is a technique to alleviate the state
explosion problem in formal verification. Constructing assumptions
for assume-guarantee reasoning however is not easy; it used to need
insights to the design and require human intervention. During the past
few years, a new technique based on machine learning was developed to
address the assumption making problem. In this talk, I will briefly
review the innovative technique and my recent works in
assume-guarantee reasoning.
Short bio
Bow-Yaw Wang received his PhD degree from the department of computer
and information science at University of Pennsylvania in 2001.
Then he joined Verplex Systems, Inc in Silicon Valley and developed a
functional property checker for hardware.
He moved to Taiwan and worked in Academia Sinica since 2003.
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