Support for Computing in Distributed Environments Based on Continuous Integration

Nowadays, tools for designing scientific applications often do not implement the required continuous integration capabilities of the applied software. Therefore, such overheads as the application development time and experiment execution makespan are substantially increased. In this regard, we propose a new approach to developing scientific applications and carrying out experiments with them. It is based on applying continuous integration to both the applied and system software in developing distributed applied software packages with a modular architecture using the Orlando Tools framework. Within the proposed approach, we provide integrating the Orlando Tools subsystems with the GitLab system and automating the development of package modules. At the same time, Orlando Tools fully support constructing and testing problem-solving schemes (workflows) that combine package modules located on environment resources with different computational characteristics. To this end, Orlando Tools provides the necessary configuring and setting up of computational resources. The practical significance of our study is substantial reduction overheads needed to experiment fulfillments and increase of the resource use efficiency.

THE SPEED CALCULATING INCREASING METHOD OF THE MARKOV MODEL NETWORK NODE

The subject of this research is the image classification methods based on a set of key points descriptors. The goal is to increase the performance of classification methods, in particular, to improve the time characteristics of classification by introducing hashing tools for reference data representation. Methods used: ORB detector and descriptors, data hashing tools, search methods in data arrays, metrics-based apparatus for determining the relevance of vectors, software modeling. The obtained results: developed an effective method of image classification based on the introduction of high-speed search using hash structures, which speeds up the calculation dozens of times; the classification time for the considered experimental descriptions increases linearly with decreasing number of hashes; the minimum metric value limit choice on setting the class for object descriptors significantly affects the accuracy of classification; the choice of such limit can be optimized for fixed samples databases; the experimentally achieved accuracy of classification indicates the efficiency of the proposed method based on data hashing. The practical significance of the work is - the classification model’s synthesis in the hash data representations space, efficiency proof of the proposed classifiers modifications on image examples, development of applied software models implementing the proposed classification methods in computer vision systems.

A Systematic Analysis of Regression Test Case Selection: A Multi-Criteria-Based Approach

In applied software engineering, the algorithms for selecting the appropriate test cases are used to perform regression testing. The key objective of this activity is to make sure that modification in the system under test (SUT) has no impact on the overall functioning of the updated software. It is concluded from the literature that the efficacy of the test case selection solely depends on the following metrics, namely, the execution cost of the test case, the lines of the code covered in unit time also known as the code coverage, the ability to capture the potential faults, and the code modifications. Furthermore, it is also observed that the approaches for the regression testing developed so far generated results by focusing on one or two parameters. In this paper, our key objectives are twofold: one is to explore the importance of the role of each metric in detail. The secondary objective is to study the combined effect of these metrics in test case selection task that is capable of achieving more than one objective. In this paper, a detailed and comprehensive review of the work related to regression testing is provided in a very distinct and principled way. This survey will be useful for the researchers contributing to the field of regression testing. It is noteworthy that our systematic literature review (SLR) included the noteworthy work published from 2007 to 2020. Our study observed that about 52 relevant studies focused on all of the four metrics to perform their respective tasks. The results also revealed that about 30% of the different categories of regression test case reported the results using metaheuristic regression test selection (RTS). Similarly, about 31% of the literature reported results using the generic regression test case selection techniques. Most of the researchers focus on the datasets, namely, Software-Artefact Infrastructure Repository (SIR), JodaTime, TreeDataStructure, and Apache Software Foundation. For validation purpose, following parameters were focused, namely, the inclusiveness, precision, recall, and retest-all.

Specifics of modern security requirements for software of electronic machine control systems

The required level of safety of machines and mechanisms is achieved through the use of appropriate safety management systems for industrial equipment, including programmable electronic ones. Such systems usually include a variety of security devices for managing industrial equipment settings. Since electronic control systems are currently considered the most promising control systems in this area, the study of the security parameters of their application support determines the relevance of this study. This study analyses the main requirements of IEC 61508 and IEC 62061 standards for compliance with modern safety requirements of embedded and applied software for electronic control systems of machines and mechanisms. This study proposes an algorithm for step-by-step implementation of software for electronic machine control systems in accordance with basic security standards for both built-in and application software. Testing has been determined as the main method of verification of application software. Based on the results of the analysis, it was found that the specification of security requirements, both built-in and application software, should highlight the necessary characteristics of each subsystem, providing information that allows choosing the equipment that meets existing security requirements. Relevant recommendations are given on the specifics of practical application of these standards.

An approach to creating application software for modeling of the deep heat processes (on the example of modeling non-stationary thermal conductivity above a mantle plume in the VLADI GEAD 4.0 MODULE)

The work substantiates the necessity and considers the methodology of own (by the researcher-modeler’s own effort) development of special applied software as a tool for modeling geological processes. The concept of a mantle plume as a system of mantle-crustal migrants, sequentially rising from the core to the fragile earth’s crust through a solid plastic mantle medium by the magma- and/or fluid fracture, is presented. A tool for computer modeling of thermal disturbance above a mantle plume in the process of its vertical development with the ability to save, process and interpret the obtained numerical and graphic information is proposed. Dependences are obtained between the depths of vertical propagation of the plume, geometric and temperature intervals of relaxation of thermal disturbance in the host medium, and geodynamic parameters. A method for assessing the thermal expansion of a medium based on the values of internal iterative variables during program execution is proposed.

Application of data hashing tools to accelerate classification decisions in structural image recognition methods

The subject of this research is the image classification methods based on a set of key points descriptors. The goal is to increase the performance of classification methods, in particular, to improve the time characteristics of classification by introducing hashing tools for reference data representation. Methods used: ORB detector and descriptors, data hashing tools, search methods in data arrays, metrics-based apparatus for determining the relevance of vectors, software modeling. The obtained results: developed an effective method of image classification based on the introduction of high-speed search using hash structures, which speeds up the calculation dozens of times; the classification time for the considered experimental descriptions increases linearly with decreasing number of hashes; the minimum metric value limit choice on setting the class for object descriptors significantly affects the accuracy of classification; the choice of such limit can be optimized for fixed samples databases; the experimentally achieved accuracy of classification indicates the efficiency of the proposed method based on data hashing. The practical significance of the work is - the classification model’s synthesis in the hash data representations space, efficiency proof of the proposed classifiers modifications on image examples, development of applied software models implementing the proposed classification methods in computer vision systems.

DEVELOPMENT AREAS OF REENGINEERING PROCESSES OF MANAGEMENT SYSTEMS IN THE CONTEXT OF INNOVATIVE ECONOMY

The authors considered anti-evolutionary, institutional, entrepreneurial and integration models of management systems in the context of studying the transformational cycle of economic processes development. This made it possible to prove that the effectiveness of the application of a specific approach to the organization of the structure of the management system depends on the degree of its implementation at a specific economic asset, and the transition to another structure is necessary in the case of the limitations of the existing one. It has been proven that one of the most promising mechanisms is the reengineering of business processes, which provides process orientation and an inductive approach to the use of modern information technologies, allowing flexible adaptation of the management system to changes in external and internal environments. The use of an object-oriented approach to the analysis, design and synthesis of applied software is proposed. It will allow the use of an iterative method of project development, which increases the efficiency, quality and speed of performing all types of work, as well as the possibility of forming multi-option solutions for the development of production and economic systems.

Static-dynamic algorithm for managing asynchronous computations in distributed environments

The paper addresses a relevant problem of computation scheduling in scientific applications (distributed applied software packages) executed in distributed environments. Forming an optimal schedule of jobs for executing of applied software (modules) is an NP-hard problem. Therefore, in practice, heuristic methods of scheduling are often used. In this regard, we propose a new static-dynamic algorithm for managing computations in heterogeneous distributed environments. The results of operating the proposed algorithm are simulated in comparison with other scenarios for computing management. They show that applying the algorithm makes it possible to achieve a rational balance between the scheduling time and the computations makespan.