Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 61 tok/s
Gemini 2.5 Pro 49 tok/s Pro
GPT-5 Medium 28 tok/s Pro
GPT-5 High 23 tok/s Pro
GPT-4o 95 tok/s Pro
Kimi K2 202 tok/s Pro
GPT OSS 120B 452 tok/s Pro
Claude Sonnet 4.5 35 tok/s Pro
2000 character limit reached

Space-Efficient Bounded Model Checking (0710.4629v1)

Published 25 Oct 2007 in cs.LO

Abstract: Current algorithms for bounded model checking use SAT methods for checking satisfiability of Boolean formulae. These methods suffer from the potential memory explosion problem. Methods based on the validity of Quantified Boolean Formulae (QBF) allow an exponentially more succinct representation of formulae to be checked, because no "unrolling" of the transition relation is required. These methods have not been widely used, because of the lack of an efficient decision procedure for QBF. We evaluate the usage of QBF in bounded model checking (BMC), using general-purpose SAT and QBF solvers. We develop a special-purpose decision procedure for QBF used in BMC, and compare our technique with the methods using general-purpose SAT and QBF solvers on real-life industrial benchmarks.

Citations (12)

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube