Survey propagation: An algorithm for satisfiability
Random Structures & Algorithms
Threshold values of random K-SAT from the cavity method
Random Structures & Algorithms
On the solution-space geometry of random constraint satisfaction problems
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
The probabilistic analysis of a greedy satisfiability algorithm
Random Structures & Algorithms
A new look at survey propagation and its generalizations
Journal of the ACM (JACM)
On the satisfiability threshold and clustering of solutions of random 3-SAT formulas
Theoretical Computer Science
On the satisfiability threshold of formulas with three literals per clause
Theoretical Computer Science
Hard and easy distributions of SAT problems
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Clustering at the phase transition
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Discrete Applied Mathematics
UBCSAT: an implementation and experimentation environment for SLS algorithms for SAT and MAX-SAT
SAT'04 Proceedings of the 7th international conference on Theory and Applications of Satisfiability Testing
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In the random k-SAT model, probabilistic calculations are often limited to the first and second moments, thus giving an idea of the average behavior, whereas what happens with high probability can significantly differ from this average behavior. In these conditions, we believe that the handiest way to understand what really happens in random k-SAT is experimenting. Experimental evidence may then give some hints hopefully leading to fruitful calculations. Also, when you design a solver, you may want to test it on real instances before you possibly prove some of its nice properties. However doing experiments can also be tedious, because you must generate random instances, then measure the properties you want to test and eventually you would even like to make your results accessible through a suitable graph. All this implies lots of repetitive tasks, and in order to automate them we developed a GUI-software called SATLab.