Introduction to SAT (constraint) solving - Crest

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SAT solver classification ◮ complete SAT solvers : based on the Davis-Putnam-Logemann-Loveland (DPLL) algorithm ◮ incomplete SAT solvers : based on local search ◮ hybrid SAT solvers
SAT solver classification Most widely used SAT solvers: ◮ Conflict-Driven Clause Learning (CDCL) SAT solvers
Page 1 and 2: Introduction to SAT (constraint) so
Page 3 and 4: The 8-queens problem
Page 5 and 6: SAT example x 1 ∨ x 2 ∨ ¬x 4
Page 7 and 8: The 8-queens problem : SAT model p
Page 9 and 10: Example background theories for SMT
Page 11 and 12: The Constraint Satisfaction Problem
Page 13 and 14: SAT, SMT or CSP ◮ SAT: + extremel
Page 15: A short introduction to SAT solving
Page 19 and 20: SAT solvers are extremely efficient
Page 23 and 24: SAT Applications ◮ Bounded Model
Page 25 and 26: CDCL SAT solver
Page 27 and 28: Unit propagation x 0 ∨ x 2 ∨ x
Page 29 and 30: Unit propagation x 0 ∨ x 2 ¬x 2
Page 31 and 32: Unit propagation x 0 ¬x 2 ∨ ¬x
Page 33 and 34: Unit propagation x 0 : satisfied ¬
Page 35 and 36: Conflict Analysis (late 90s) MiniSA
Page 37 and 38: Conflict Analysis - conflict clause
Page 39 and 40: SAT, SMT and CSP solvers are used f
Page 43 and 44: References ◮ Armin Biere, ed. Han

Introduction to SAT (constraint) solving - Crest

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