This section deals with the issues of business continuity and recovery after disasters. The authors analyzed standards, laws, and regulations pertaining to the parameters of periodic monitoring and recovery in information systems. This section includes mathematical models of resources and environment periodic monitoring as well as periodic backup and recovery after interruptions or disasters. The work demonstrates that the well-known deterministic periodic monitoring and backup models do not take into account stochastic peculiarities of ergatic systems to the full extent. The authors developed new stochastic models of restricted monitoring and backup that allow taking into consideration resources constrains and random factors of information systems operation. The notion of Bernoulli stream has been introduced. This section suggests the criteria for selecting deterministic or stochastic monitoring and backup models and their combinations. A solution of direct and reverse task of the calculation of control and monitoring procedures frequency is offered. This section also provides a methodology for information system stability management, considering periodic monitoring, rollback, and recovery in case of interruption.
The work describes reliability and security growth models for modifiable software systems as a result of revisions and tests performed for specified input data areas. The work shows that the known reliability growth models are of monotonically increasing type, which is not in line with current multi-version team technologies of software development that are primarily based on the open-source code. The authors suggest new nonmonotonically increasing models of software reliability evaluation and planning that allow taking into account the effect of decreased reliability resulting from updates or wavefront errors. The work describes the elaborated bigeminal and generic reliability evaluation model as well as the models and test planning procedures. The work includes calculated expressions for the evaluation of the model accuracy and shows that the developed models are adequate to real data. An example is given of transition from probability models to fuzzy models in case of incomplete basic data. The work provides general recommendations for selection of software tool testing models.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.