Передмова

Передмова до матеріалів семінарів.Preface to workshop proceedings

Передмова

It is a brief description of the Volume II of the proceedings of ICTERI 2021.Дається короткий опис тому ІІ збірника матеріалів конференції ICTERI 2021

Software failures prediction using RBF neural network

One of the prospective techniques for software reliability prediction are those based on nonparametric models, in particular on artificial neural networks. In this paper the study of influence of number of input neurons of network based on radial basis function on the efficiency of software failures prediction presented in the form of time series is carried out. Software faults time series are constructed using Chromium and Chromium-OS open source software systems testing data with proposed further processing as a normalized values of the number of software failures in equal intervals, followed by transfer to man-days. It is demonstrated that the closest prediction can be achieved using Inverse Multiquadric activation function with 10…20 input layer neurons and 30 hidden neurons

A Comprehensive Model of Android Software Aging and Rejuvenation Considering Battery Saving

The more complex the software system, the greater the number of possible combinations of defects that can cause errors, resulting in software defects that are difficult to isolate and expensive to correct in the development stage. An essential feature of such defects is a gradual deterioration in software performance finishing with software failure—software aging. Mobile devices are particularly vulnerable to software aging. Thus, there is a constant need for methods and tools to eliminate the effects of aging in mobile systems based on modeling the aging process, including the study of metrics and aging factors and the development of more reliable and adequate aging and rejuvenation models. This paper summarizes the previously developed Android software aging and rejuvenation models and presents a comprehensive model of aging and rejuvenation for the Android operating system. The comprehensive model is based on continuous-time Markov Chains and considers different aging levels, mobile device activity, and battery status. The aging and rejuvenation model can be used to assess the software quality, allows obtaining expressions for indicators of software rejuvenation efficiency, and can be used to design and select parameters of the software rejuvenation method considering battery saving