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An Experimental Evaluation of Conflict Diagnosis and Recursive Learning in Boolean Satisfiability
 

Summary: IWLS'00
Page 1
An Experimental Evaluation of Conflict Diagnosis and
Recursive Learning in Boolean Satisfiability
Fadi A. Aloul and Karem A. Sakallah
Department of Electrical Engineering and Computer Science
University of Michigan
AnnArbor, MI 48109-2122
{faloul, karem}@eecs.umich.edu
Abstract: Interest in propositional satisfiability (SAT) has been on the rise lately, spurred in part
by the recent availability of powerful solvers that are sufficiently efficient and robust to deal with
the large-scale SAT problems that typically arise in electronic design automation application. In
this paper we experimentally compare two recent search procedures: recursive learning and con-
flict diagnosis. Both techniques can be viewed as a form of dynamic identification of "useful"
implicates of the function being tested. We also examine the performance of the basic Davis-Put-
nam search on variants of the input formula that are augmented statically, in a pre-processing
step, with additional clauses. The broad conclusions of the paper are that supplanting the input
formula with more clauses has the potential of significantly reducing the search effort. This gain,
however, must be weighed against the extra effort required to generate the additional clauses.
Dynamic clause identification, therefore, is generally more effective than a static pre-processing

  

Source: Aloul, Fadi - Department of Computer Engineering, American University of Sharjah

 

Collections: Engineering