=Paper= {{Paper |id=Vol-2013/paper5 |storemode=property |title=None |pdfUrl=https://ceur-ws.org/Vol-2013/paper5.pdf |volume=Vol-2013 }} ==None== https://ceur-ws.org/Vol-2013/paper5.pdf
                                                                                    9

              Elimination Techniques
      in Modern Propositional Logic Reasoning
            (Abstract of Invited Talk)
                                 Norbert Manthey

                           nmanthey@conp-solutions.com

The satisfiability testing (SAT) problem is one of the most relevant problems of
computer science, as SAT is the representative problem for the complexity class
N P [3]. Due to the numerous improvements to SAT solvers, many industrial
problems are successfully reduced to SAT [3]. The highly optimized and special-
ized SAT solvers make these improvements accessible, and with such systems
solving problems via SAT became effective.
    Many recent improvements in SAT solvers are related to data structures,
search heuristics or problem simplifications. However, the major reasoning tech-
niques in propositional logic is resolution on clauses, used in unit propagation,
variable elimination as well as clause learning [6, 7, 13]. State-of-the-art SAT
solvers primarily use this technique to guide their search [1].
    Both from a reasoning strength, as well as from an empirical analysis point of
view, these systems still benefit from further problem simplifications, specifically
variable elimination, where elimination is not only performed on pure clauses,
but also on XOR constraints as well as cardinality constraints [2, 4, 8, 14]. For
the two more expressive constraint types, constraints can even be extracted from
formulas in CNF.
    The relations between formulas F before and after F 0 a simplification have
been described in [11]. For applied SAT solving, not only performance matters,
but also the ability of constructing models for the original formula F based on
a model for F 0 . All above mentioned elimination techniques have this property.
    Further simplification techniques rely on removing clauses, e.g. blocked clause
elimination [9]. From a proof complexity point of view, the counter technique –
adding blocked clauses [10] – can lead to a much more powerful reasoning than
resolution, namely introducing fresh variables via extended resolution [5]. At-
tempts on introducing fresh variables automatically exist [12], but are currently
more used during encoding a problem into CNF than as a reasoning technique
during search. Again, a model for the original formula can always be constructed
based on a model of the simplified formula.


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Copyright c 2017 by the paper’s authors
In: P. Koopmann, S. Rudolph, R. Schmidt, C. Wernhard (eds.): SOQE 2017 – Pro-
ceedings of the Workshop on Second-Order Quantifier Elimination and Related Topics,
Dresden, Germany, December 6–8, 2017, published at http://ceur-ws.org.
                                                                                     10

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