Digital Transformation of the master's course "Structural Analysis of Systems"

The paper discusses the digitalization of the teaching process for the Master's course "Structural Analysis of Systems." Over the course of one semester, students explore research issues, quantitative assessment, and analysis of the efficiency (including flexibility, reliability, and safety) of economic, technical, organizational, human-machine, and other types of complex systems. During the teaching process, the practical tasks of quantitative evaluation criteria of efficiency were solved manually, which required a lot of lecture time and less time was left for analysis. In order to increase the effectiveness of teaching, as a result of the implementation of the internal university grant project, a special web application and a new manual with practical exercises were created. Now the students perform the tasks of quantitative evaluation of the system efficiency criteria using the web application based on logical-probabilistic methods, models and algorithms. The practical task in the web application is carried out in the following order: 1) Building a graphical scheme of system reliability and security models; 2) Determination of logical functions of the shortest paths for the successful functioning of the system and their representation in disjunctive normal form (DNF); 3) Input of logical functions received in the form of disjunctive normal form to the application as initial data; 4) Transformation of DNF into orthogonal disjunction normal form (ODNF) using the orthogonalization algorithm; 5) Replacing logical variables with probabilistic data in ODNF and probabilistic assessment of reliability/safety; 6) Ranking and constructing a diagram of probabilistic estimates of the shortest paths of the successful functioning of the system; 7) Calculation of the "weight" of each element in system reliability and structural analysis of system.As a result, using the web application, the learning process became more efficient, productive and interesting. Students were given the opportunity to solve a large number of varied and complex tasks during the learning process. In addition, students successfully use the new teaching technology in the process of preparing semester abstracts, conference presentations, articles, master's and doctoral theses.