Analysis of Methods and Models for the Verification of Complex Information-Analytical Systems for Intelligent Monitoring

ABSTRACT Modern information and analytical systems for information and technological support of intelligent security monitoring systems are distinguished by a comprehensive approach to integrating disparate measurement and telecommunications systems. They are characterized by a high degree of complexity, distribution, and dynamism, which significantly increases the requirements for ensuring their accuracy and reliability. Traditional testing methods cannot fully guarantee the absence of critical errors across all stages of the information-analytical system lifecycle. Consequently, the use of verification methods and models—focused on analyzing system properties during the design and development phases—has become particularly relevant. An analysis of existing methods and models for the verification of complex information-analytical systems is conducted to identify their advantages, limitations, and areas of applicability, as well as to determine ways to enhance the efficiency of verification processes amidst the increasing complexity of software solutions. This paper reviews and systematizes verification methods for complex information and analytical systems (IAS), covering informal, semi-formal, and formal approaches. It examines automated tools supporting verification processes as well as model-based methods relying on formal mathematical models. The potential for applying model-based verification to assess the functional and non-functional characteristics of IAS is also analyzed.