Complex Software Research Articles

An empirical analysis of feature selection techniques for Software Defect Prediction

<p>Detecting software defects before they occur is crucial in software engineering as it impacts software system quality and reliability. Previous studies on predicting software defects have typically employed software features, such as code size, complexity, coupling, cohesion, inheritance, and other software metrics., to forecast whether a code file or commit is prone to defects in the future. However, it is advantageous to restrict the number of features employed in a defect prediction model to avoid the challenges associated with multicollinearity and the “curse of dimensionality” and to simplify the data analysis process. By using a reduced number of features, the defect prediction model can concentrate on the most significant variables and improve its accuracy. This research paper investigates the impact of eight feature selection methods on the accuracy and stability of six supervised learning models. This study is novel as it is based on exhaustive experimentation of each of the eight feature selection techniques with each of the six supervised learning models. Two notable findings have been obtained. First, we discovered that the association and coherence-based techniques have demonstrated the highest level of accuracy when it comes to defect prediction. The models that utilized these selected features outperformed those using the original features. Second, the feature selection techniques, namely Correlation feature selection, Recursive feature elimination, and Ridge feature selection when combined with the Support vector machine and Decision tree classifier, consistently selected low-variance features across multiple supervised defect prediction models. When combined with different classifiers, these techniques achieved exceptional performance on the publicly available NASA datasets CM1 and PC2. The findings revealed a remarkable accuracy rate of over 85% for CM1 and 95% for PC2, accompanied by precision, recall, and f-measure values exceeding 95%. These exceptional results indicate the achievement of the highest level of performance in the evaluation.</p>

Edge IoT Prototyping Using Model-Driven Representations: A Use Case for Smart Agriculture.

Industry 4.0 is positioned at the junction of different disciplines, aiming to re-engineer processes and improve effectiveness and efficiency. It is taking over many industries whose traditional practices are being disrupted by advances in technology and inter-connectivity. In this context, enhanced agriculture systems incorporate new components that are capable of generating better decision making (humidity/temperature/soil sensors, drones for plague detection, smart irrigation, etc.) and also include novel processes for crop control (reproducible environmental conditions, proven strategies for water stress, etc.). At the same time, advances in model-driven development (MDD) simplify software development by introducing domain-specific abstractions of the code that makes application development feasible for domain experts who cannot code. XMDD (eXtreme MDD) makes this way to assemble software even more user-friendly and enables application domain experts who are not programmers to create complex solutions in a more straightforward way. Key to this approach is the introduction of high-level representations of domain-specific functionalities (called SIBs, service-independent building blocks) that encapsulate the programming code and their organisation in reusable libraries, and they are made available in the application development environment. This way, new domain-specific abstractions of the code become easily comprehensible and composable by domain experts. In this paper, we apply these concepts to a smart agriculture solution, producing a proof of concept for the new methodology in this application domain to be used as a portable demonstrator for MDD in IoT and agriculture in the Confirm Research Centre for Smart Manufacturing. Together with model-driven development tools, we leverage here the capabilities of the Nordic Thingy:53 as a multi-protocol IoT prototyping platform. It is an advanced sensing device that handles the data collection and distribution for decision making in the context of the agricultural system and supports edge computing. We demonstrate the importance of high-level abstraction when adopting a complex software development cycle within a multilayered heterogeneous IT ecosystem.

A Comparative Study of Commit Representations for JIT Vulnerability Prediction

With the evolution of software systems, their size and complexity are rising rapidly. Identifying vulnerabilities as early as possible is crucial for ensuring high software quality and security. Just-in-time (JIT) vulnerability prediction, which aims to find vulnerabilities at the time of commit, has increasingly become a focus of attention. In our work, we present a comparative study to provide insights into the current state of JIT vulnerability prediction by examining three candidate models: CC2Vec, DeepJIT, and Code Change Tree. These unique approaches aptly represent the various techniques used in the field, allowing us to offer a thorough description of the current limitations and strengths of JIT vulnerability prediction. Our focus was on the predictive power of the models, their usability in terms of false positive (FP) rates, and the granularity of the source code analysis they are capable of handling. For training and evaluation, we used two recently published datasets containing vulnerability-inducing commits: ProjectKB and Defectors. Our results highlight the trade-offs between predictive accuracy and operational flexibility and also provide guidance on the use of ML-based automation for developers, especially considering false positive rates in commit-based vulnerability prediction. These findings can serve as crucial insights for future research and practical applications in software security.

An OTA Upgrade Differential Compression Algorithm Based on Suffix Array Induced Sorting and BsDiff Methods

As the scale and complexity of software for industrial equipment increases, the risk of defects being introduced into the software also increases. Over-the-air (OTA) technology eliminates software defects by regularly updating and maintaining the software equipment. However, downloading an upgraded file is time-consuming. The differential compression algorithm can rapidly complete OTA software upgrades. To solve the low-efficiency problem of suffix array sorting in the BsDiff algorithm, a fusion algorithm based on the suffix array induced sorting and BsDiff methods was proposed to reduce the time consumption in the OTA upgrade process. The execution of the difference algorithm in the cloud was simulated using bench experiments. Subsequently, the function and performance of the proposed algorithm were experimentally evaluated. The results showed that the optimized algorithm could save more than 35% of the time compared to the original algorithm, which improved the OTA upgrade efficiency to a certain extent.

Case study on communicating with research ethics committees about minimizing risk through software: an application for record linkage in secondary data analysis.

In retrospective secondary data analysis studies, researchers often seek waiver of consent from institutional Review Boards (IRB) and minimize risk by utilizing complex software. Yet, little is known about the perspectives of IRB experts on these approaches. To facilitate effective communication about risk mitigation strategies using software, we conducted two studies with IRB experts to co-create appropriate language when describing a software to IRBs. We conducted structured focus groups with IRB experts to solicit ideas on questions regarding benefits, risks, and informational needs. Based on these results, we developed a template IRB application and template responses for a generic study using privacy-enhancing software. We then conducted a three-round Delphi study to refine the template IRB application and the template responses based on expert panel feedback. To facilitate participants' deliberation, we shared the revisions and a summary of participants' feedback during each Delphi round. 11 experts in two focus groups generated 13 ideas on risks, benefits, and informational needs. 17 experts participated in the Delphi study with 13 completing all rounds. Most agreed that privacy-enhancing software will minimize risk, but regardless all secondary data studies have an inherent risk of unexpected disclosures. The majority (84.6%) noted that subjects in retrospective secondary data studies experience no greater risks than the risks experienced in ordinary life in the modern digital society. Hence, all retrospective data-only studies with no contact with subjects would be minimal risk studies. First, we found fundamental disagreements in how some IRB experts view risks in secondary data research. Such disagreements are consequential because they can affect determination outcomes and might suggest IRBs at different institutions might come to different conclusions regarding similar study protocols. Second, the highest ranked risks and benefits of privacy-enhancing software in our study were societal rather than individual. The highest ranked benefits were facilitating more research and promoting responsible data governance practices. The highest ranked risks were risk of invalid results from systematic user error or erroneous algorithms. These societal considerations are typically more characteristic of public health ethics as opposed to the bioethical approach of research ethics, possibly reflecting the difficulty applying a bioethical approach (eg, informed consent) in secondary data studies. Finally, the development of privacy-enhancing technology for secondary data research depends on effective communication and collaboration between the privacy experts and technology developers. Privacy is a complex issue that requires a holistic approach that is best addressed through privacy-by-design principles. Privacy expert participation is important yet often neglected in this design process. This study suggests best practice strategies for engaging the privacy community through co-developing companion documents for software through participatory design to facilitate transparency and communication. In this case study, the final template IRB application and responses we released with the open-source software can be easily adapted by researchers to better communicate with their IRB when using the software. This can help increase responsible data governance practices when many software developers are not research ethics experts.

Experimental studies of the control process of the working body of a single-bucket excavator

The operator's actions are studied when controlling a single-bucket excavator when digging a trench for underground pipeline laying. The angular parameters of the working body of a single-bucket excavator are obtained. The time of the full cycle of soil development and the main elements of the software and hardware complex for collecting and processing data are determined. The dependence of the time of a technological operation on the angular parameter of the working body of the excavator is obtained. Keywords single-bucket excavator, trench, working body, operator, hardware and software complex

Discursive Modulation in Open Source Software: How Online Communities Shape Novelty and Complexity

We study the development of two open source software (OSS) web frameworks to understand how OSS communities shape software novelty and complexity in the absence of strong organizational hierarchies. We examine how projects engage in distinct “discursive modulation practices” to imprint the community’s shared core doctrines and design principles onto the software thereby shaping its novelty and complexity. We borrow the concept of modulation from audio synthesis to explain how a pre-existing signal—in our case, the ongoing community discourse—gets modulated to produce varying sounds—in our case the novelty and complexity of the software. The concept of modulation offers a lens to understand how emergent, community-wide development activities are influenced by filtering of discursive positions and mixing of those positions, thereby shaping the artifact’s novelty and complexity. Our research shows that the modulation of novelty exhibits a range from “proximal” to “distal” searches for new features, while the modulation of complexity varies between “integration” and “deprecation.” By drawing on these concepts, we formulate a theory that explains how modulation results in alternative OSS community approaches to shaping software novelty and complexity, and how this process reflects, and is reflected in, the resulting software artifact.

Efficient Rollout of a Dynamic Optimization Algorithm

A successful deployment process of a complex software solution, such as optimization algorithms in a dynamic production environment is an extremely complicated and time-consuming task. Over this, the acceptance by those employees where the software solution is to be used later should not be underestimated; it is essential to involve them in the entire development process, as they can be game changers. This paper summarizes some best practices and lessons learned about the full integration of an optimization algorithm in the dynamic steelmaking environment of voestalpine Stahl GmbH. The focus is on the development of a practical test strategy and ultimately a generally valid rollout concept for an arbitrary complex software system for every conceivable industry. Over that, emerging gaps between theory and practice are highlighted, an attempt is made to justify their cause, and, as a result, possible solutions to tackle those challenges are presented.

ЗАКОНОМЕРНОСТИ ПОКАЗАТЕЛЯ ТРАНСПОРТНОГО ЗАТОРА НА НЕКОТОРЫХ ПЕРЕСЕЧЕНИЯХ УЛИЧНО-ДОРОЖНОЙ СЕТИ

The average speed and density of road transport are used as indicators of the congestion situation, but do not allow tracking the evolution (stages of formatting, progressing, and vanishing) of traffic congestion. The authors proposed and justified a quantitative indicator of traffic congestion, which allows in an automated mode to identify the congestion situation on the urban road network using hardware and software video recording systems. The purpose of this study is due to the need to study the quantitative characteristics of the proposed indicator at characteristic intersections of urban roads, which will allow us to develop scientifically based recommendations for predicting congestion situations, substantiating, and making optimal decisions on measures to promptly eliminate traffic congestion. The object of study is the traffic flow at three types of intersections of the Perm city road network, equipped with a photo and video recording software and hardware complex. The subject of the study is the regularities of the evolution of the listed deterministic indicators of traffic flows, which can be used for operational forecasting of the formation, development, and elimination of traffic congestion. The theoretical and methodological approach is based on the methods of mathematical statistics used to process the results of observations of traffic flows at different types of intersections using a «sliding window», calculating the average daily value and standard deviation. The initial data were obtained with the help of hardware and software complexes for fixing violations of traffic rules installed on the street and road network of the Perm city. As a result of the study, the rational parameters of the «sliding window» were determined, ensuring the structuring of the traffic congestion indicator; the facts of the congestion situations formation were revealed; the features of the congestion evolution and the presence of problematic traffic directions for which it is advisable to change the traffic light regulation mode were determined. The theoretical and practical significance of the work consists in checking the operability of the proposed indicator and criterion of traffic congestion, which is of practical interest from the point of view of predicting anomalies in the movement of vehicles on the road network, adjusting the operating modes of traffic lights, etc. It is also possible to use the proposed traffic congestion indicator to assess the effectiveness of traffic light regulation on the Perm city road network. The direction of further research is to study the patterns of traffic congestion at intersections of the urban road network, of various types that are not included in this study.

IIOT ПЕРЕДАЧА ДАННЫХ С БПЛА В ПРОМЫШЛЕННУЮ СРЕДУ АГРОКОМПЛЕКСОВ В РЕЖИМЕ РЕАЛЬНОГО ВРЕМЕНИ

Agricultural complexes, including agriculture, are a good environment for the introduction of modern technologies and methods of using unmanned aerial vehicles to solve various tasks. Currently, in distributed control systems in various agricultural complexes using unmanned aerial vehicles, the classical hardware and software architecture for building such systems has been established. However, this approach has a number of significant drawbacks. (Research purpose) The research purpose is selecting the IIoT of the wireless real-time communication protocol of unmanned aerial vehicles for irrigation of agricultural complexes with a ground-based industrial system and developing concepts of a hardware and software complex using modern technologies and practices of the industrial Internet of things. (Materials and methods) Used open sources of international communities in the field of automation and the industrial Internet of Things, as well as domestic and foreign scientific publications on these topics, as source data and materials for the analysis and design of the proposed hardware architecture of the IIoT platform. The method of decomposition according to automation levels was applied; the method of decomposition according to the functionality performed by individual hardware and software components of the system; the method of summarizing information from modern sources on the subject of research; formalization of the hardware and software structure in the form of schematic diagrams. (Results and discussions) Proposed the concept of information data transmission based on the IIoT protocol of DDS-real-time data transmission. (Conclusions) It has been shown that classical architectural approaches to data transmission in the conditions of wireless systems and agro-unmanned aircraft have proven themselves well, however, the need to introduce new architectural and software methods and protocols for data transmission in real time leads to the need to study promising ways to implement this functionality. We analyzed the existing global trends in the field under consideration and proposed an up-to-date and up-to-date concept of IIoT architecture of distributed data transmission systems within the framework of a distributed management and monitoring system for agricultural complexes based on unmanned aircraft.

Hardware and software complex for creating a digital passport of an athlete’smotor stereotype

The key feature of the dynamic stereotype in sports is that it is formed asstable only for standard movements, in the case of situational movements it has labilityand is determined by temporal and spatial characteristics. A more in-depth study of biomechanical processes within the framework of the athlete’s motor stereotype allows us to develop and implement effective approaches to preparing for competitive activity,as well as to form ideas about the recovery of athletes after injuries and competitions. Currently, in the process of training athletes, digital technologies are increasingly being used to create an up-to-date digital passport of athletes’ motor activity. The article presents modern data on the use of a software and hardware complex in the process ofcreating a digital passport of an athlete’s motor stereotype.

A modern approach to sports selection of children

The purpose of the study is to consider modern approaches to the selection of sports-gifted children and to justify the effectiveness of the introduction of a model for the selection of sports-gifted children with the determination of their sports orientation based on the use of the hardware and software complex "Become a champion". The article defines the stages of sports selection and presents a methodology for studying sports predisposition with using the complex "Become a champion".

Assessing the reliability of the hardware and software complex of fault-tolerant control systems

Reliability assessment of hardware and software complexes is relevant due to the expansion of automation and intellectualization for sustainable development of mining and transport systems, energy complexes and mechanical engineering. This paper presents an approach to the reliability assessment of control systems based on functional block diagrams of software and control flows. When assessing the reliability of a control system, software is considered taking into account the close relationship with hardware. The article considers control systems that assume the performance of the required function periodically and repeatedly within the transportation and technological cycle of the system. This is typical for automation of mining and transportation systems, as well as energy complexes. It is taken into account that the main function within the transportation-technological cycle does not require a complex algorithm in contrast to the operating system. Thus, the proposed reliability assessment model allows to take into account the interaction between hardware and software of automated control systems, including the variant of their faulttolerant execution.

РАЗРАБОТКА КОНСТРУКЦИИ И ОБОСНОВАНИЕ ПАРАМЕТРОВ РАБОТЫ ПАСТЕРИЗАТОРА С ИНДУКЦИОННЫМ НАГРЕВОМ

The use of induction heating for pasteurization of food raw materials is proposed. (Purpose of the study) Creation of an energy-efficient method of heat treatment of food raw materials using a pasteurization tank heated by induction currents. (Materials and methods) The pasteurization container is made of AISI 304 stainless steel. Plates made of AISI 430 ferritic stainless steel are welded on the tank to localize the induction heating site. The frame for the inductor was developed using the Fusion 360 automated programming system and printed on a 3D printer made of a polymer material, the choice of which is determined by the maximum operating temperature. A litecenter is selected as the winding of the inductor. Attention is paid to the constructive solution of the location of inductors. The design of the basic electrical circuit of the power part of the prototype device was carried out in the multifunctional program for computer-aided design of electronic circuits Proteus 7.10. (Results and discussion) A prototype induction type installation for pasteurization of food raw materials has been developed. The proposed solution for the arrangement of inductors leads to uniform and rapid heating of the container material and, accordingly, the raw materials in contact with it. The choice of a litzendrate in the manufacture of an inductor made it possible to increase the quality factor at the operating (resonant) frequency of the power unit. Using a thermal imager, thermographic images show a change in the thermal field when the container is heated by different devices. At the same time, the time to reach the required heating temperature with the help of the developed inductor system increases. To control the operation of the prototype pasteurization device, a hardware and software complex has been developed that allows you to set pasteurization parameters, control the process and create a report on the pasteurization session. Thanks to the developed control system, the electromagnetic field can be precisely controlled, which makes it possible to easily heat a small area of the material to a high temperature without affecting the surrounding space. (Conclusions) The proposed pasteurization method is more energy efficient than other methods such as resistive heating, since less energy is required for the same amount of material. The use of induction heating for pasteurization plants of raw materials allows them to be made energy efficient, less bulky, and more environmentally friendly.

Building a Flexible and Resource-Light Monitoring Platform for a WLCG-Tier2

Software development projects at Edinburgh identified a desire to build and manage our own monitoring platform. This better allows us to support the developing and varied physics and computing interests of our Experimental Particle Physics group. This production platform enables oversight of international experimental data management, local software development projects and active monitoring of lab facilities within our research group. Larger sites such as CERN have access to many resources to support generalpurpose centralised monitoring solutions such as MONIT. At a WLCG Tier2 we only have access to a fraction of these resources and manpower. Recycling nodes from grid storage and borrowed capacity from our Tier2 Hypervisors has enabled us to build a reliable monitoring infrastructure. This also contributes back to our Tier2 management improving our operational and security monitoring. Shared experiences from larger sites gave us a head-start in building our own service monitoring (FluentD) and multi-protocol (AMQP/STOMP/UDP datagram) messaging frameworks atop both our Elasticsearch and OpenSearch clusters. This has been built with minimal hardware and software complexity, maximising maintainability, and reducing manpower costs. A secondary design goal has also been the ability to migrate and upgrade individual components with minimal service interruption. To achieve this, we made heavy use of different layers of containerisation (Podman/Docker), virtualization and NGINX web proxies. This presentation details our experiences in developing this platform from scratch with a focus on minimal resource use. This includes lessons learnt in deploying and comparing both an Elasticsearch and OpenSearch clusters, as well as designing various levels of automation and resiliency for our monitoring framework. This has culminated in us effectively indexing, parsing and storing >200GB of logging and monitoring data per day.

Signal modeling of means of tacit information acquisition using spline functions

The article deals with the problem of recognizing signals from systems of unauthorized covert acquisition of confidential information. The general problem of detecting signals from the means of covert information acquisition (CIL) consists in the direct formation of a technique that would allow submitting the detected signal from CIL using the legal data transmission range in an analytical form convenient for further analysis and direct detection of a malicious signal. An analysis of the meaning, signs and properties of the means of covertly obtaining information was carried out, and their unmasking signs were presented. An overview of the methods used to record the detected signals from the means of covert information acquisition in an analytical form convenient for further analysis is carried out. Methods of analytical representation of the detected signal in the form of a composition of continuous functions and in the form of a spline function of two variables were analyzed. In order to increase the effectiveness of signal recognition of means of covert information obtaining, a method of constructing a ZNOI signal in the form of a two-dimensional spline function or a tensor product of two one-dimensional spline spaces is proposed. This method makes it possible to improve the efficiency of recognition of ZNOI signals and its automation. It is shown that an important condition for the recognition of a probable signal of a digital ZNOI is finding the maximum energy of the spectrum, which in turn makes it possible to apply the criteria of mathematical analysis of reaching the extrema of the function. The use of such a mathematical apparatus makes it possible, using the existing technical and software complexes, to automate the process of recognition of ZNOI signals.

Boosting and Comparing Performance of Machine Learning Classifiers with Meta-heuristic Techniques to Detect Code Smell

Background: Continuous modifications, suboptimal software design practices, and stringent project deadlines contribute to the proliferation of code smells. Detecting and refactoring these code smells are pivotal to maintaining complex and essential software systems. Neglecting them may lead to future software defects, rendering systems challenging to maintain, and eventually obsolete. Supervised machine learning techniques have emerged as valuable tools for classifying code smells without needing expert knowledge or fixed threshold values. Further enhancement of classifier performance can be achieved through effective feature selection techniques and the optimization of hyperparameter values. Aim: Performance measures of multiple machine learning classifiers are improved by fine tuning its hyperparameters using various type of meta-heuristic algorithms including swarm intelligent, physics, math, and bio-based etc. Their performance measures are compared to find the best meta-heuristic algorithm in the context of code smell detection and its impact is evaluated based on statistical tests. Method: This study employs sixteen contemporary and robust meta-heuristic algorithms to optimize the hyperparameters of two machine learning algorithms: Support Vector Machine (SVM) and k-nearest Neighbors (k-NN). The No Free Lunch theorem underscores that the success of an optimization algorithm in one application may not necessarily extend to others. Consequently, a rigorous comparative analysis of these algorithms is undertaken to identify the best-fit solutions for code smell detection. A diverse range of optimization algorithms, encompassing Arithmetic, Jellyfish Search, Flow Direction, Student Psychology Based, Pathfinder, Sine Cosine, Jaya, Crow Search, Dragonfly, Krill Herd, Multi-Verse, Symbiotic Organisms Search, Flower Pollination, Teaching Learning Based, Gravitational Search, and Biogeography-Based Optimization, have been implemented. Results: In the case of optimized SVM, the highest attained accuracy, AUC, and F-measure values are 98.75%, 100%, and 98.57%, respectively. Remarkably, significant increases in accuracy and AUC, reaching 32.22% and 45.11% respectively, are observed. For k-NN, the best accuracy, AUC, and F-measure values are all perfect at 100%, with noteworthy hikes in accuracy and ROC-AUC values, amounting to 43.89% and 40.83%, respectively. Conclusion: Optimized SVM exhibits exceptional performance with the Sine Cosine Optimization algorithm, while k-NN attains its peak performance with the Flower Optimization algorithm. Statistical analysis underscores the substantial impact of employing meta-heuristic algorithms for optimizing machine learning classifiers, enhancing their performance significantly. Optimized SVM excels in detecting the God Class, while optimized k-NN is particularly effective in identifying the Data Class. This innovative fusion automates the tuning process and elevates classifier performance, simultaneously addressing multiple longstanding challenges.

Optimization of the current spray angle of the nozzles of the adaptive distribution system of a single-support boom sprayer

One of the unsolved problems of plant protection mechanization is the uneven distribution of pesticides due to vertical vibrations of the sprayer boom. At the same time, the variation of the treatment band with each sprayer can reach 38% or more. This issue is even more relevant for single-support wheelbarrow sprayers, which are used in breeding and primary seed production. This significantly affects the quality of the technological operation. A technical solution to this problem could be the use of sprayers with variable spray geometry. Such a solution requires an analytical substantiation of the dependence of the spray pattern angle on the position angle of the sprayer boom. The purpose of the proposed research is to develop a technique for optimizing the spray angle of sprayer nozzles, taking into account the vertical vibrations of the distribution rod. Geometric and mathematical modeling, theoretical analysis of qualitative and agrotechnical parameters of spraying, substantiation of the laws of the technological process of spraying based on the known laws of physics and classical mathematics, as well as a method of nomogramming functions of several variables were used as scientific methods. It has been established that the uniformity of the application of protective equipment is determined not only by the position of the rod in the vertical plane, but also by the value of the root spray angle, the height of the installation of the sprayer and its position relative to the center of oscillation of the rod. An analytical expression is derived that relates the current width of the processing strip from one sprayer to the specified factors. The dependence of the optimal spray angle on the angle of inclination of the sprayer boom is also proposed. A nomogram has been developed that takes into account permissible deviations in the uneven distribution of the working fluid during spraying. The optimization technique is new. It is applicable to the development of software for the sprayer control complex, which is equipped with an adaptive pesticide distribution system in changing conditions.

The concept of architectural reliability of software for ensuring the functioning of request-free measuring stations

The article proposes the concept of architectural reliability of software included in the hardware and software complex of request-free measuring stations. This concept is based on previously completed activities to shape the appearance of a complex of hardware and software for the functioning of measuring stations. It is noted that in order to solve problems related to increasing the architectural reliability of software, the security functions and information and logical interaction of the components of the measuring station are essential. Since software architecture is determined by the concept of architectural design, the work presents the stages of designing a complex software system. The description provided includes the basic operations of architectural design, with decomposition necessary to structure and organize system specifications. The final stage lists the main steps that should be taken to enhance the strategic influence of the software architecture on the functionality and reliability of the set of technical means for ensuring the operation of request-free measuring stations.

ПРАКТИЧЕСКАЯ РЕАЛИЗАЦИЯ ПРИНЦИПОВ ИНТЕЛЛЕКТУАЛЬНОГО УПРАВЛЕНИЯ ТРАНСПОРТНЫМИ ПОТОКАМИ В ГОРОДЕ БЕЛГОРОДЕ

Within the framework of the presented research, the issues of the fundamental principles of the implementation of intelligent traffic management are considered. Innovative mechanisms for monitoring traffic speeds and traffic intensity, tracking car routes implemented within the framework of the intelligent transport system of the Belgorod urban agglomeration are presented. The positive effect of the implementation of these software and hardware complexes on key sections of the road network is calculated.