The formalization method
Formalization is the representation of any content area (reasoning, evidence, classification procedures, etc.) in the form of a formal system.
The formal system is a sign model that defines a set of objects by describing the source objects and the rules for building new ones.
Language is the sign system that allows you to carry out information exchange in any social system. Along with natural languages in computer science, formal languages have also been developed: number systems, propositional algebras, programming languages.
Formal languages are used to construct formalological models.
In the general theory of law, there is a direction called "formalization of legal norms". The formalization of the legal norm is the identification of its logical structure, the logical rules for deducing judgments.
So, OA Gavrilov proposed using logical operations to simulate the logical structure of the legal norm. The purpose of modeling is to identify logical (including latent) links of the legal norm. The logical structure of the legal norm can be represented in the following form:
where p - the hypothesis of the norm; d - disposition; s is a sanction.
Formalization makes it possible to systematize, clarify and methodologically clarify the legal theory, to reveal the nature of the interrelationships between its various legal prescriptions, to identify and formulate existing unsolved problems.
Formalization assumes the strengthening of the role of formal logic as the basis of legal science. The formalization of the language of law makes it possible to model and analyze some legal norms with the help of such a new class of automated legal information systems as expert systems.
Algorithmization and programming method
The word algorithm appeared as a result of the Latin transcription of the name of the great scientist IX c. Al Khorezmi, who formulated general rules (algorithms) for performing arithmetic operations on decimal numbers.
Algorithm is a certain sequence of actions, the performance of which leads to the achievement of the goal.
Essential requirements that should be met when developing algorithms are:
- discreteness. The process of solving a problem is described by some set of actions. Executing an action is one step from the original data to the original results. The objects of the action at each step are finite quantities.
Thus, the discreteness property of algorithms is manifested in the fact that the procedure for solving the problem itself breaks up into a sequence of steps (discretization in time), and at each step a piece of information of finite volume (discretization by size) is processed;
- finiteness. First, the execution of the algorithm must be completed by obtaining the desired result in a finite number of steps. Secondly, the set of actions from which any algorithm can be constructed is also finite;
- certainty. The actions at each step of the algorithm must be strictly defined, i.e. the description of this or that stage of computation can not be arbitrarily interpreted. In addition, the relationship between the stages (the order of their succession) should be determined for any possible options for the development of the computational process. It is the certainty of the algorithm that makes it possible to entrust its implementation to an automaton that does not know how to act in situations that are not completely defined.
Each algorithm is associated with a set of values that are acceptable for it as the source data. Similarly, the execution of the algorithm is completed by obtaining results relating to the set of output values that are acceptable for the problem being solved.
Programming is the implementation of a given algorithm in a formal programming language. Programming allows you to shift the conduct and analysis of information processes to modern computing equipment.
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