Software & Systems

Articles of journal № 4 at 2023 year.

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1. Automatic runtime error localization for software debugging using neural networks [№4 за 2023 год]
Authors: Dostovalova, A.M., Sherminskaya, A.A.
Visitors: 1253
A new automatic runtime error localization method using a neural network was developed. The method determines bug position by program functions tracing data. The method matches an error containing probability for each function. This probability is proportional to the effect of each function parameter on a program execution result. A numerical characteristic calculated by Hashem algorithm determines a parameter effect. The method was applied for debugging several programs with nested functions. The most probable bug locations defined by the method were compared with their real positions. The developed method has some features. It is able to localize multiple bugs, nested function bugs, and bugs with unequal manifestation and location places. In all cases, bugged parameters had more weight in comparison with rest parameters. At the same time, method determines a full error trace for each bug. The trace consists of all program parameters related to a bug. Therefore, the method is able to localize logical errors in program. The method can be used for debugging both technical system software and hardware since method logic does not depend on source data.

2. Extracting subsystems from a multilevel representation of a Boolean function system for joint logical minimization [№4 за 2023 год]
Authors: Bibilo, P.N., Kirienko, N.A., Romanov, V.I.
Visitors: 1395
The paper presents experimental results obtained from studying the effectiveness of programs for minimizing multilevel algebraic representations of Boolean function systems performed in combinational circuit synthesis. The resulting minimized logical descriptions are presented as Shannon expansion formulas or formulas defining Boolean networks. Three approaches are investigated: joint minimization of multilevel representations of Boolean function systems; separate minimization; selection of connected subsystems from an original system, where each connected subsystem is minimized separately, however functions that make up each subsystem are minimized together. After obtaining minimized descriptions of circuits given as a set of interrelated Shannon expansion formulas or as two-operand logical equations corresponding to Boolean networks, the synthesis of logic circuits is performed within the same library for designing custom digital CMOS VLSI (very large integrated circuits made using complementary metal oxide-semiconductor technology). The resulting logic circuits are compared in terms of a crystal area and speed (time delay). Experiments involve 39 industrial examples of circuits. Experimental results show competitiveness and expediency of all three considered approaches in practice. The improvement of circuit parameters (area, time delay) in approach 3 is achieved due to minimizing each selected subsystem on the basis of Shannon expansions in its own (for each subsystem) permutation of expansion variables. At the same time, minimizing multilevel representations based on Shannon expansions for function system matrix descriptions is more effective for one half of circuits; minimizing based on Shannon expansions of function systems presented as logical equations is effective for the other half. The practical significance of the study is that the developed software, which implements the proposed algorithm for extracting Boolean function subsystems, allows reducing the area and increasing the performance of functional blocks of custom CMOS VLSI in many cases.

3. Neural network-based approach for identifying fake news [№4 за 2023 год]
Authors: Tumbinskaya, M.V., Galiev, R.A.
Visitors: 1069
Currently, telecommunication facilities actively disseminate news. Identification of fake news based on their headlines has become a relevant problem. The purpose of this study is to increase a user information reliability level in browser environment. Automated recognition of fake news based on their headlines in the browser environment can achieve this goal. The paper proposes using neural networks that allow analyzing fake news headlines semantically and processing large amounts of data. The article examines popular foreign and domestic web resources for identifying fake news, their distinctive features. The authors carried out an analysis and selected neural network models BERT-MLP, BERT-CNN, BERT-LSTM to be a basis for developing a web resource. They used samples of Russian-language news headlines to train neural network models. An experimental study was carried out to assess the quality and adequacy of neural network models on test and validation data samples including news headlines on various topics. The developed web resource based on the BERT-CNN, BERT-GRU, BERT-LSTM models showed good results. The reliability of identifying fake news was 86,29%. The practical value of the work is in the fact that the developed web resource can be used as a tool for recognizing fake news by specialists in counteracting destructive political technologies, as well as information security specialists. To im-prove classification accuracy, it is advisable to expand a training data set, which allows identifying more complex dependencies in data.

4. Integration of reinforcement learning methods and fuzzy logic for intelligent real-time systems [№4 за 2023 год]
Authors: Eremeev, A.P. , Sergeev, M.D., Petrov, V.S.
Visitors: 1294
The paper considers the possibilities of integrating reinforcement learning methods and fuzzy logic in terms of improving the efficiency of reinforcement learning algorithms. The main focus is on applying such integrated methods in real-time intelligent systems, especially in decision support systems for monitoring and controlling complex technical objects. The basis is a reinforcement learning method based on temporal differences; an environmental state and the reward signal are formed using fuzzy logic. The paper presents software implementation and the data of computer simulation of deep learning methods with reinforcement based on temporal differences obtained from a comparative analysis of a fuzzy logic algorithm and neural network algorithms. The authors of the paper show that the main advantages of reinforcement learning algorithms using fuzzy logic are: training effectiveness in terms of minimizing the number of episodes, which is especially important regarding the availability of limited data for training or rapid adaptation of real-time training; resistance to noise and outliers in data, which is important in real environments with noise or data changes; interpretability - fuzzy logic algorithms provide interpretable rules and conclusions based on fuzzy logic; extension of a reinforcement learning scope to subject/problem areas and tasks with a continuous state space. These researches and developments are carried out in terms of designing intelligent real-time decision support systems. Such systems are designed to help operational dispatch personnel (decision makers) in monitoring and managing complex technical and organizational systems under fairly severe time constraints and various types of uncertainties (inaccuracies, fuzziness, inconsistencies) in the information entering a system, i.e. in the presence of so-called noisy data.

5. Using MPI library for parallel implementation of a brute-force algorithm [№4 за 2023 год]
Authors: Aye Min Thike, Lupin, S.A., Fedyashin, D.A.
Visitors: 1256
The paper presents results of studying the effectiveness of a parallel application for solving a quadratic assignment problem. The application uses a brute-force algorithm and a Message Passing Interface (MPI) to ensure interprocess communication in a distributed computing environment. Solution options are generated by a lexicographic permutation method, which is well parallelized and ensures load balancing of nodes. The range of brute-force algorithm use to large scale optimization problems is expanded by dividing a search space into parts, which significantly reduces the number of options under consideration. The experiments were conducted in a distributed environment containing 50 nodes with the 7th generation Intel ® Core ™ i5 processors. A parallel application for solving a large-scale problem (n = 24) demonstrated the possibility accelerating calculations in the range from 99 to 95 % from the maximum possible one; an exact solution was found in all cases. This confirms the correctness of methods used for load distribution and for computational complex-ity reduction of tasks. Further work will be aimed at exploring the possibility of using the proposed approaches to implementing a brute-force algorithm and as hybrid applications, which is relevant for heterogeneous computing environments. Since a quadratic assignment problem is a discrete optimization problem, the obtained results suggest that the proposed approaches are effective for other problems of this class.

6. Quantum algorithmic gate-based computing: Grover quantum search algorithm design in quantum software engineering [№4 за 2023 год]
Authors: Ulyanov, S.V., Ulyanov, V.S.
Visitors: 1222
The difference between classical and quantum algorithms (QA) is following: problem solved by QA is coded in the structure of the quantum operators. Input to QA in this case is always the same. Output of QA says which problem coded. In some sense, give a function to QA to analyze and QA returns its property as an answer without quantitative computing. QA studies qualitative properties of the functions. The core of any QA is a set of unitary quantum operators or quantum gates. In practical representation, quantum gate is a unitary matrix with particular structure. The size of this matrix grows exponentially with an increase in the number of inputs, which significantly limits the QA simulation on a classical computer with von Neumann architecture. Quantum search algorithm (QSA) – models apply for the solution of computer science problems as searching in unstructured data base, quantum cryptography, engineering tasks, control system design, robotics, smart controllers, etc. Grover’s algorithm is explained in details along with implementations on a local computer simulator. The presented article describes a practical approach to modeling one of the most famous QA on classical computers, the Grover algorithm.

7. Simulation of hydraulic actuator dynamics in virtual environment systems [№4 за 2023 год]
Authors: Strashnov, E.V., Mironenko, I.N.
Visitors: 1017
The development of computer graphics and computing machinery has led to active using of virtual environment systems in many areas of human activity. In particular, virtual (computer) training complexes for simulation and control of complex mechanical systems are widely used. Some of these systems are equipped with hydraulic actuators. This paper considers real-time simulation of hydraulic actuators dynamics in virtual environment systems. The authors propose solving this problem based on an approach with co-simulation dynamics of hydraulic actuators and articulated rigid bodies. To this end, the authors used a sequential impulses method that resulted in obtaining coordinates and velocities of piston and two linked bodies. The approach assumes that, first, piston velocity is computed by integrating hydraulic equations using a semi-implicit Euler scheme without taking load into account. Then, the obtained velocity is adjusted by an impulse that limits velocities of a piston and two linked bodies. The proposed approach is iterative and makes it possible to implement dynamics of articulated body systems with a hydraulic actuator in real time. The main result of the study is in flexibility of the developed approach for simulating hydraulic actuator dynamics based on a sequential impulses method; it allows ensuring all constraints in a multibody system in a unified way. Unlike other similar solutions, this approach does not require cumbersome matrix calculations and solving large dimension linear equation systems. Approbation in the created VirSim software package showed adequacy and effectiveness of the solutions proposed in the paper. The practical significance of the work is that the proposed methods and approaches for simulating hydraulic actuators dynamics can be used in simulators for training operators of skills for controlling robots, machines of various types, mechanisms, equipment, etc.

8. Russian import-substitution structure based on an optimal distribution system model [№4 за 2023 год]
Authors: Abu-Abed, F.N., Zhironkin, S.A.
Visitors: 1151
The study focuses on a model of an optimal distribution system of economy investments that requires import substitution due to external shocks and sanctions. It is necessary to build a mathematical model that links a sectoral structure of investment and output in terms of technological limitations. This paper explores possibilities of using economic structure and dynamics models for import substitution purposes; using a production function for this purposes, dynamic stochastic general equilibrium models and Bayesian vector autoregressions. This paper presents author's method based on constructing a decision tree for enumerating bypass cycles – route options with a cut. The proposed method can be modified to reduce its running time. The recommended technology for constructing an import substitution structure model is initially reduced to constructing its objective function and presenting it in a graph form. Subsequently, based on a data structure for building routes, the authors present an algorithm that is a basis for implementing optimal distribution of investments in an industry structure and for monitoring their compliance with the designated import substitution requirements. This algorithm is a basis for a software tool architecture and structure with corresponding classes, which provides output as an investment-industry correspondence. The results obtained are necessary for developing a software tool that can solve the important industry problem of modeling an import substitution structure based on investment distribution by industries and products, as well as predict the impact of new external shocks and technological restrictions on this process, changes in labor productivity and a production capacity utilization level.

9. On an interuniversity quantum network project [№4 за 2023 год]
Authors: Ovsyannikov, A.P., Shabanov, B.M.
Visitors: 785
The paper discusses the issues of creating an interuniversity quantum network, a so-called national infrastructure testbed for quantum key distribution (QKD). It is designed for testing solutions for building networks with quantum key distribution, equipment checking and benchmarking in practice, education and personnel training. Currently all advanced countries are showing interest in creating QKD networks. Russia developed its own QKD equipment and is building a backbone QKD quantum network. A Concept for creating, developing and operating an Interuniversity Quantum Network (IUQN) based on a National Research Computer Network (NICS) was developed in order to accelerate practical implementation of quantum communications and to solve a variety of related research, technical, regulatory and personnel issues. A pilot project of the IUQN was developed as a part of implementing the concept. IUQN connects universities and scientific organizations that have their own quantum communication infrastructure, have competencies in quantum technologies, conduct research and development and train specialists in this field. The paper describes IUQN topology, gives QKD and data exchange schemes. When considering various QKD schemes, minimal requirements for trusted intermediate nodes protection are preferred. The paper proposes to consider using MDI-QKD protocol through untrusted nodes. The authors briefly describe Russian QKD equipment planned to use in IUQN. The use of equipment from all three Russian manufacturers in IUQN will allow demonstrating the possibilities of scaling quantum networks on each equipment type, explore the possibilities of different manufacturers’ equipment collaboration and adapt it to joint use. It is planned to implement the pilot project of creating IUQN in 2023-2024.

10. Information security of a supercomputer center [№4 за 2023 год]
Authors: Baranov, A.V., Korepanov, P.M., Kuznetsov, E.E.
Visitors: 1083
Most scientific supercomputer centers (SC) process open access information. Typically, they use standard information security technologies built into operating systems, data storage, and network devices. In recent years we can see an increase in both the number of information security threats and computer attacks and incidents against SCs, which causes reputational and financial risks for SCs. The paper discusses information processing features in SC, which significantly limit known information security measures and tools. Such features include SC user’s freedom to choose tools and application software packages to solve their research problems; a need to ensure maximum computing performance of super-computer resources provided to users; a limited use of secure operating systems and software update tools. The paper justifies the relevance of developing a complex system approach to SC information security. An adequate level of SC information security must be ensured without significant restrictions of user abilities and reducing the quality of high-performance computing services provided to users. The paper discusses current threats to SC information security, provides a classification of data processed in SC, and defines a list of current information security measures. The proposed optional SC information security system structure takes into account the reviewed features of SC information security. The proposed approach is based on dividing SC computing infrastructure into security zones and on using network perimeter control tools, as well as access and information security event analysis.

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