Balancing scalability and uniformity in SAT witness generator
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[1] Yehuda Naveh,et al. Constraint-Based Random Stimuli Generation for Hardware Verification , 2006, AI Mag..
[2] Toniann Pitassi,et al. Algorithms and complexity results for #SAT and Bayesian inference , 2003, 44th Annual IEEE Symposium on Foundations of Computer Science, 2003. Proceedings..
[3] Andreas Kuehlmann,et al. Stimulus generation for constrained random simulation , 2007, 2007 IEEE/ACM International Conference on Computer-Aided Design.
[4] Supratik Chakraborty,et al. A Scalable and Nearly Uniform Generator of SAT Witnesses , 2013, CAV.
[5] Sharad Malik,et al. Chaff: engineering an efficient SAT solver , 2001, Proceedings of the 38th Design Automation Conference (IEEE Cat. No.01CH37232).
[6] Bart Selman,et al. A New Approach to Model Counting , 2005, SAT.
[7] Vibhav Gogate,et al. A New Algorithm for Sampling CSP Solutions Uniformly at Random , 2006, CP.
[8] C. D. Gelatt,et al. Optimization by Simulated Annealing , 1983, Science.
[9] Jinian Bian,et al. Self-adjusting constrained random stimulus generation using splitting evenness evaluation and XOR constraints , 2009, 2009 Asia and South Pacific Design Automation Conference.
[10] Bart Selman,et al. Towards Efficient Sampling: Exploiting Random Walk Strategies , 2004, AAAI.
[11] Nathan Kitchen. Markov Chain Monte Carlo Stimulus Generation for Constrained Random Simulation , 2010 .
[12] Bart Selman,et al. Embed and Project: Discrete Sampling with Universal Hashing , 2013, NIPS.
[13] Igor L. Markov,et al. Random Stimulus Generation using Entropy and XOR Constraints , 2008, 2008 Design, Automation and Test in Europe.
[14] Supratik Chakraborty,et al. A Scalable Approximate Model Counter , 2013, CP.
[15] Rina Dechter,et al. Generating random solutions for constraint satisfaction problems , 2002, AAAI/IAAI.
[16] Mihir Bellare,et al. Uniform Generation of NP-Witnesses Using an NP-Oracle , 2000, Inf. Comput..
[17] Bart Selman,et al. Near-Uniform Sampling of Combinatorial Spaces Using XOR Constraints , 2006, NIPS.
[18] Dan Roth,et al. On the Hardness of Approximate Reasoning , 1993, IJCAI.
[19] Leslie G. Valiant,et al. Random Generation of Combinatorial Structures from a Uniform Distribution , 1986, Theor. Comput. Sci..
[20] Harry Foster,et al. Principles of verifiable RTL design - a functional coding style supporting verification processes in Verilog , 2000 .
[21] C. Pixley,et al. Simplifying Boolean constraint solving for random simulation-vector generation , 2002, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.
[22] Jörg Hoffmann,et al. Short XORs for Model Counting: From Theory to Practice , 2007, SAT.
[23] Michael Sipser,et al. A complexity theoretic approach to randomness , 1983, STOC.
[24] Mahesh A. Iyer,et al. Race a word-level atpg-based constraints solver system for smart random simulation , 2003, International Test Conference, 2003. Proceedings. ITC 2003..
[25] Thomas R. Shiple,et al. Building Circuits from Relations , 2000, CAV.