[Resource Topic] 2017/244: Model-counting Approaches For Nonlinear Numerical Constraints

Welcome to the resource topic for 2017/244

Title:
Model-counting Approaches For Nonlinear Numerical Constraints

Authors: Mateus Borges, Quoc-Sang Phan, Antonio Filieri, Corina S. Păsăreanu

Abstract:

Model counting is of central importance in quantitative reasoning about systems. Examples include computing the probability that a system successfully accomplishes its task without errors, and measuring the number of bits leaked by a system to an adversary in Shannon entropy. Most previous work in those areas demonstrated their analysis on programs with linear constraints, in which cases model counting is polynomial time. Model counting for nonlinear constraints is notoriously hard, and thus programs with nonlinear constraints are not well-studied. This paper surveys state-of-the-art techniques and tools for model counting with respect to SMT constraints, modulo the bitvector theory, since this theory is decidable, and it can express nonlinear constraints that arise from the analysis of computer programs. We integrate these techniques within the Symbolic Pathfinder platform and evaluate them on difficult nonlinear constraints generated from the analysis of cryptographic functions.

ePrint: https://eprint.iacr.org/2017/244

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