The directions of perspective research in the field of analysis and modeling of the dynamics of time series of processes in complex systems with the presence of the human factor are described. The dynamics of processes in such systems is described by nonstationary time series. Predicting the evolution of such systems is of great importance for managing processes in social (election campaigns), economic (stock, futures and commodity markets) and socio-technical systems (social networks). The general information on time series and tasks of their analysis is given. Modern methods of time series analysis for economic processes are considered. The results show that economic processes cannot be considered completely random, since they tend to self-organize and, moreover, are subject to the influence of memory of previous states. It was revealed that one of the main tasks in modeling processes in sociotechnical systems (for example, social networks) is the development of a mathematical apparatus for bringing data to a single measurement scale. The modern models of analysis and forecasting of electoral processes based on the analysis of time series: structural, polling, hybrid. Based on the analysis, their advantages and disadvantages are considered. In conclusion, it was concluded that to describe processes in complex systems with the presence of the human factor, in addition to traditional factors, it is necessary to develop and use methods and tools to take into account the possibility of self-organization of human groups and the presence of memory about previous states of the system.

Enterprise software system (ESS) development is essentially complicated by increasing amount of data, its exponential growth and heterogeneous nature of systems components concerning to systems structuring and architecture. However, it appears that an integrated approach to ESS lifecycle support (including mathematical models and supporting CASE-tools) could help to outline component-level metadata pattern design. These patterns allow to efficiently organize ESS lifecycle by increasing the reuse of the software artifacts and by accelerating ESS adaptation to rapidly changing business requirements. The paper outlines the approach and discusses its possible implementations.

В статье обсуждается задача проверки гипотез о типе распределения данных, получаемых при измерениях в образовании, в программных системах. Приведён обзор критериев проверки нормальности, имеющих дискретные аппроксимации, что делает их пригодными для реализации в программных системах. Обсуждается место и необходимость применения указанных критериев при автоматизации измерений в образовании. Результаты обзора положены в основу алгоритма подбора критерия или группы критериев в программной системе, ориентированной на измерения в образовании.