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Thursday, March 6 • 4:30pm - 6:30pm
Poster: Sampling Techniques for Boolean Satisfiability, Kuldeep Meel, Rice University

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Boolean satisfiability (SAT) has played a key role in diverse areas spanning testing, formal verification, planning, optimization, inferencing and the like. Apart from the classical problem of checking boolean satisfiability, the problems of generating satisfying uniformly at random, and of counting the total number of satisfying assignments have also attracted significant theoretical and practical interest over the years. Prior work offered heuristic approaches with very weak or no guarantee of performance, and theoretical approaches with proven guarantees, but poor performance in practice. We propose a novel approach based on limited-independence hashing that allows us to design algorithms for both problems, with strong theoretical guarantees and scalability extending to thousands of variables. Based on this approach, we present two practical algorithms, UniWit: a near uniform generator and ApproxMC: the first scalable approximate model counter, along with reference implementations. Our algorithms work by issuing polynomial calls to SAT solver. We demonstrate scalability of our algorithms over a large set of benchmarks arising from different application domains.


Kuldeep Meel

Graduate Student, Rice University
Kuldeep is a PhD student in Rice working with Prof. Moshe Vardi and Supratik Chakraborty and obtained his B.Tech. from IIT Bombay in 2012. His research broadly falls into the intersection of program synthesis, computer-aided verification and formal methods. He is the recipient of 2013 Andrew Ladd fellowship.

Thursday March 6, 2014 4:30pm - 6:30pm
BRC Exhibit Hall Rice University 6500 Main Street at University, Houston, TX 77030