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New CSB tool enhances SMT solvers for bit-vector counting and sampling

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new tool called CSB designed to enhance Satisfiability modulo theory (SMT) solvers. This tool extends SMT capabilities beyond simple satisfiability to include model counting and sampling for bit-vectors. CSB achieves this by converting bit-vector formulas into Conjunctive Normal Form (CNF) using bit-blasting techniques, which are then processed by existing CNF model counters and samplers. Experimental results indicate that CSB offers significant performance gains compared to previous methods. AI

IMPACT Introduces new capabilities for automated reasoning tools used in AI research.

RANK_REASON The cluster describes a new tool and methodology presented in a research paper on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New CSB tool enhances SMT solvers for bit-vector counting and sampling

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The cluster describes a new tool and methodology presented in a research paper on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Arijit Shaw, Kuldeep S. Meel ·

    CSB: A Counting and Sampling tool for Bit-vectors

    arXiv:2607.04142v1 Announce Type: cross Abstract: Satisfiability modulo theory (SMT) solvers have significantly advanced automated reasoning due to their effectiveness in solving problems across various fields. With the advancement in SMT solvers, there is growing interest in exp…

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