text: In the present paper we describe the technology for translating algorithmic descriptions of discrete functions to SAT. The proposed technology is aimed at applications in algebraic cryptanalysis. We describe how cryptanalysis instances are reduced to SAT in such a way that it should be perceived as natural by the cryptographic community. Therefore, in the theoretical part of the paper we justify the main principles of general reduction to SAT for discrete functions from a class containing the majority of functions employed in cryptography. Based on these principles we describe the Transalg software system, developed with SAT-based cryptanalysis specifics in mind. We show the results of applications of Transalg to construction of a number of attacks on various cryptographic functions. Some of the corresponding attacks are state of the art. We also compare the functional capabilities of the proposed system with that of other software systems that can be used to reduce cryptanalysis instances to SAT, and also with the CBMC system widely employed in symbolic verification. In the paper we also present vast experimental data, obtained using the SAT-solvers that took first places at the SAT-competitions in the recent several years.
  @cite_43: This paper describes the symbolic execution of programs. Instead of supplying the normal inputs to a program (e.g. numbers) one supplies symbols representing arbitrary values. The execution proceeds as in a normal execution except that values may be symbolic formulas over the input symbols. The difficult, yet interesting issues arise during the symbolic execution of conditional branch type statements. A particular system called EFFIGY which provides symbolic execution for program testing and debugging is also described. It interpretively executes programs written in a simple PL I style programming language. It includes many standard debugging features, the ability to manage and to prove things about symbolic expressions, a simple program testing manager, and a program verifier. A brief discussion of the relationship between symbolic execution and program proving is also included.
  @cite_68: 
  @cite_74: It is shown that any recognition problem solved by a polynomial time-bounded nondeterministic Turing machine can be “reduced” to the problem of determining whether a given propositional formula is a tautology. Here “reduced” means, roughly speaking, that the first problem can be solved deterministically in polynomial time provided an oracle is available for solving the second. From this notion of reducible, polynomial degrees of difficulty are defined, and it is shown that the problem of determining tautologyhood has the same polynomial degree as the problem of determining whether the first of two given graphs is isomorphic to a subgraph of the second. Other examples are discussed. A method of measuring the complexity of proof procedures for the predicate calculus is introduced and discussed.
summary: In the basis of , and other systems lies the ideology of symbolic execution of a program specifying a considered function. Note that the idea to transform programs to Boolean formulas was first proposed by S.A. Cook in his paper @cite_74 which led to the creation and development of the theory of NP-completeness. The notion "Symbolic Execution" first appeared in the paper @cite_43 by J.C. King, where it is defined as a process of interpretation of a program in a special extended semantics, within the context of which it is allowed to take symbols as input and put formulas as output. Currently, symbolic execution using SAT is actively used in software verification (see for example @cite_68 ).