ETAPS 2019
Sat 6 - Thu 11 April 2019 Prague, Czech Republic
Mon 8 Apr 2019 11:30 - 12:00 at SUN I - SAT and SMT I Chair(s): Lijun Zhang

Satisfaction-Driven Clause Learning (SDCL) is a recent SAT solving paradigm that aggressively trims the search space of possible truth assignments. To determine whether the SAT solver is currently exploring a dispensable part of the search space, SDCL makes use of the so-called positive reduct of a formula: The positive reduct is an easily solvable propositional formula that is satisfiable if the current assignment of the solver can be safely pruned from the search space. In this paper, we present two novel variants of the positive reduct that allow for even more aggressive pruning. Using one of these variants allows SDCL to solve harder problems, in particular the well-known Tseitin formulas. For the first time, we were able to generate and automatically check clausal proofs of these problems.

Mon 8 Apr

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

10:30 - 12:30
SAT and SMT ITACAS at SUN I
Chair(s): Lijun Zhang Chinese Academy of Sciences
10:30
30m
Talk
Decomposing Farkas Interpolants
TACAS
Martin Blicha USI Lugano, Switzerland, Antti Hyvärinen , Jan Kofroň Charles University, Natasha Sharygina USI Lugano, Switzerland
Link to publication
11:00
30m
Talk
Parallel SAT Simplification on GPU Architectures
TACAS
Muhammad Osama Eindhoven University of Technology, Anton Wijs Eindhoven University of Technology
Link to publication
11:30
30m
Talk
Encoding Redundancy for Satisfaction-Driven Clause LearningBest paper nomination
TACAS
Marijn Heule The University of Texas at Austin, Benjamin Kiesl CISPA Helmholtz Center for Information Security, Armin Biere Johannes Kepler University Linz
Link to publication
12:00
30m
Talk
WAPS: Weighted and Projected Sampling
TACAS
Rahul Gupta , Shubham Sharma , Subhajit Roy IIT Kanpur, India, Kuldeep S. Meel National University of Singapore
Link to publication