Software Architecture Research Articles

Pendampingan Mahasiswa MBKM KKNT dalam Perencanaan Daerah Wisata Kuta Rayat, Kecamatan Naman Teran, Kabupaten Karo

The village tourism program continues to grow as alternative tourism is expected to make a positive contribution to community development. Efforts to develop and manage resources must be directed so that they can fulfill economic, social, and aesthetic aspects while maintaining the integrity and or preservation of ecology, biodiversity, culture, and living systems. Kuta Rayat is one of the villages in the Naman Teran sub-district, Karo Regency, North Sumatra Province, Indonesia. Kuta Rayat Village is one of the villages planned to become a tourist village. The mentoring activities were carried out in 2023 and involved academics and students of the Architectural Engineering Study Programme of Universitas Panca Budi Medan. The mentoring method was carried out through Focus Group Discussion (FGD). The results of the assistance explained that tourism villages have an important role for many aspects, one of which is spurring the potential for the growth of the creative economy in the local environment, as well as opening up employment opportunities for residents who are close to tourist sites. Kuta Rayat Village has a lot of potential to be developed into a tourist area. Through the development of the potential of existing resources, villages in Indonesia, especially the Karo Regency area, are expected to become attractive and sustainable tourist destinations and the main target of tourism village development is to improve the welfare of the surrounding community.

An orbit determination software suite for Space Surveillance and Tracking applications

The growth of both operational satellites and orbital debris is creating the requirement for more robust Space Surveillance and Tracking (SST)-related applications. These systems necessarily must leverage ground-based sensors (optical and radar) to realise higher performance solutions. In this context, the European Union Space Surveillance and Tracking (EUSST) consortium groups European national agencies and institutions, and is in charge of carrying out the following services: conjunction analysis, fragmentation analysis and re-entry prediction, and the Italian Air Force is in charge of the latter two. In this framework, the Italian SST Operational Centre (ISOC) has recently upgraded its system to the ISOC Suite, an integrated platform providing multiple functions and services in the SST domain. This paper presents the orbit determination functions provided by the novel ISOC Suite. First, a statistical index is computed to assess the measurements correlation to a catalogued object. If it is successful, the object predicted orbit is refined through measurements according either to batch or sequential filters; otherwise these are used to refine a first estimate of the target orbital state computed according to dedicated methodologies. After the presentation of the prototypal software architecture, the ISOC Suite performance are assessed and discussed both in terms of synthetic and real data.

System software architecture for advancing human robot interaction by cloud services and multi-robot cooperation

Human-like interactions with robots based on Conversational AI facilitate assistance and teamwork in various contexts. Those interactions are further enhanced by utilizing physical presence and context from the robot's hardware. Robot cooperation is also especially useful, when software or hardware resources have to be shared in a multi-robot system. Therefore, we propose a modular software architecture for multi-robot cooperation that extends the integration of Conversational AI into Socially Assistive Robots, previously suggested by authors. It utilizes a flow-based approach that involves shared repositories and direct or message-driven communication to convey natural language transcriptions among robots in order to support their cooperation. By experiments we evaluated the cooperation between NAOqi based robots and Furhat robot. Our experimental results demonstrate architecture's modularity and adaptability to different cloud services, along with its effectiveness for interactions involving multiple robots.

TEACHING AND APPLYING WATER CONSUMPTION SIMULTANEITY IN RESIDENTIAL: AN ACTIVE LEARNING PROJECT-BASED ENGINEERING APPROACH

In the present project, spanning from April 2020 to August 2022, the study focused on Hydraulic Engineering I within the Civil Engineering program and the Hydrosanitary Installation Project in the Architecture program. The objectives included calculating the simultaneity coefficient and determining the maximum probable flow for each student's residence. To achieve these objectives, active learning methodologies, specifically project-based learning (PBL), were adeptly employed to enrich students' practical knowledge and foster collaboration. The process began with architectural surveys of residential properties, followed by inventories of pipes, sanitary appliances, and wet rooms. Measurements of flow rates at various faucet openings (25%, 50%, 75%, and 100%) were conducted, along with the recording of operating pressures within home networks. This data served as the foundation for creating calibration curves, a process carried out over 120 days. Using the collected data, each student developed a hydraulic model of their network and compared the software results to practical measurements. The participants calculated the simultaneity coefficient (Ks) and maximum possible flow for their dwellings using hydraulic design concepts and regulatory standards. The results were documented in technical reports, a video tutorial, and infographics. The research highlights the importance of understanding residential water usage patterns and their potential for optimizing water delivery systems. It also underscores the value of experiential learning, which helps students bridge theory and practice, enhancing technical skills and their understanding of hydraulic engineering.

An efficient high performance reconfigurable canonical sign digit architecture for software defined radio

Software defined radios (SDRs) are highly motivated for wireless device modelling due to their flexibility and scalability over alternative wireless design options. The evolutionary structure of finite impulse response (FIR) filters was designed for a proposed reconfigurable canonical sign digit (CSD) approach. Considering the complex trade-off, this is accomplished with many FIR taps, which is a challenging assignment. On the baseband processing side, design is given with parameterization-controlled FIR filter tap selection. Optimal processing models to overcome the reconfigurable design issues associated with the SDR system for a multi-standard wireless communication system root cosine filter standard are often used to implement multiple FIR channelization topologies, each of which is tied to a particular in-phase and quadrature (IQ) symbol. Additionally, it demonstrates the viability of using a multi-modulation baseband modulator in the SDR system for next-generation wireless communication systems to maximise adaptability with the least amount of computational complexity overhead. The proposed multiplier-less FIR filter-based reconfigurable baseband modulator, according to the experimental results, offers a 6% complexity reduction and a 47% improvement in performance efficiency over the current SDR system.

Overall Scheme Design of Fault Diagnosis for Complex Electronic Systems

Traditional manual testing methods are no longer able to meet the maintenance needs of modern shipboard fire control system board-level circuits. Therefore, the development of intelligent and universal automatic test systems has become an important issue for shipboard fire control system fault detection. This article analyzes the performance and functional requirements of the automatic test system, develops the automatic test system based on PXI bus instruments, and designs an overall solution with signal time-frequency analysis capabilities that can carry out intelligent fault diagnosis for a variety of board-level circuits. On this basis, the design of hardware circuit and software solution is completed. The automatic test system was analyzed on hardware indicators and software functions. On the hardware side, the hardware resource selection was completed based on the hardware indicator requirements. On the software side, the overall software architecture design and the design of each functional module were completed based on the system software functional requirements. Finally, the composition and functions of each module of the system software and the overall operation process are introduced.

Software Architecture for Agricultural Robots: Systems, Requirements, Challenges, Case Studies, and Future Perspectives

Software Architecture for Agricultural Robots: Systems, Requirements, Challenges, Case Studies, and Future Perspectives

VDMNav: Software Architecture for Aerodynamically Constrained Navigation on Small Fixed-Wing Drones

VDMNav: Software Architecture for Aerodynamically Constrained Navigation on Small Fixed-Wing Drones

Lamarckian Platform: Pushing the Boundaries of Evolutionary Reinforcement Learning Toward Asynchronous Commercial Games

Despite the emerging progress of integrating evolutionary computation into reinforcement learning, the absence of a high-performance platform endowing composability and massive parallelism causes non-trivial difficulties for research and applications related to asynchronous commercial games. Here we introduce Lamarckian <xref ref-type="fn" rid="fn1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">¹</xref> <fn id="fn1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><label>¹</label> The code and demonstrational setup of Lamarckian are publicly available at <uri>https://github. com/lamarckian/lamarckian</uri>. </fn> – an open-source platform featuring support for evolutionary reinforcement learning scalable to distributed computing resources. To improve the training speed and data efficiency, Lamarckian adopts optimized communication methods and an asynchronous evolutionary reinforcement learning workflow. To meet the demand for an asynchronous interface by commercial games and various methods, Lamarckian tailors an asynchronous Markov Decision Process interface and designs an object-oriented software architecture with decoupled modules. In comparison with the state-of-the-art RLlib, we empirically demonstrate the unique advantages of Lamarckian on benchmark tests with up to 6000 CPU cores: i) both the sampling efficiency and training speed are doubled when running PPO on Google football game; ii) the training speed is 13 times faster when running PBT+PPO on Pong game. Moreover, we also present two use cases: i) how Lamarckian is applied to generating behavior-diverse game AI; ii) how Lamarckian is applied to game balancing tests for an asynchronous commercial game.

Unveiling Faulty User Sequences: A Model-Based Approach to Test Three-Tier Software Architectures

Context:When testing three-tiered architectures, strategies often rely on superficial information, e.g., black-box input. However, the correct behavior of software-intensive systems based on such architectural pattern also depends on the logic hidden behind the interface. Verifying the response process is thus often complex and requires ad-hoc strategies. Objective:We propose an approach to identify faults hidden behind the presentation layer. The model-based approach uses an architectural abstraction called managed component Data Flow Graph (mcDFG). The mcDFG is aware of the interactions between all layers of the architecture and guides the generation of tests based on different mcDFG coverage criteria to identify faults in the business logic. Method:To evaluate the approach viability, we consider a three-tiered web application and 32 faults. The fault detection capability is assessed by comparing a set of test suites created by following our method and a set of test suites developed by utilizing traditional testing strategies. Results:The collected data show that the proposed model-based approach is a viable option to identify faults hidden in the logic layer, as it can outperform standard strategies based solely on the presentation layer while keeping the number of test cases and number of interactions per test case low.

ARCHITECTURE PRACTICAL LEARNING: ANALYSIS OF ARCHITECTURAL DESIGN STUDIO THROUGH A NEUROSCIENCE EDUCATION PERSPECTIVE

During the Architecture and Urban Design IV studio (DAU IV), within the second year of the Architecture program (PUCE-FADA), the students most build and apply diverse construction systems in a project; we have noticed that manual knowledge is being lost. In the curricular design of architectural workshops most of the projects are based on digital media, yet analogical tools, like our own hands, could be vital to develop a broad experience in construction and a critical thinking. Due to this, the new curriculum has an emphasis in construction practice. Through a perspective of neuroscience education, this paper analyzes the program and the exercises developed during the studio. Some of the neuroscience pedagogic principles will evaluate the DAU IV studio: emotions and learning, real-life experiences, contextual learning and intrinsic motivation. The authors then critically review which of the activities developed are suitable and encouraging for addressing a practical learning. Recommendations will be outlined for future versions of the studio.

АРХІТЕКТУРА ПРОГРАМНОЇ СИСТЕМИ ДЛЯ ВИРІШЕННЯ ЗАДАЧІ КЛАСИФІКАЦІЇ НА ОСНОВІ ПРИВАТНИХ ДАНИХ

Data analysis and artificial intelligence systems are becoming widely used in various spheres of human life. This is confirmed by more typical cases of their use, in particular, the selection of recommendations for the user in e-commerce, the detection of spam in e-mail services, and the moderation of user comments; as well as cases of personal use of such tools (for example, chatbots ChatGPT, Google Bard, Microsoft Copilot have appeared and gained significant popularity in the last two years). One of the key elements of such systems is data, which is necessary for training and testing software systems of intelligent data analysis. A significant amount of diverse data contributes to the construction of a software system with high accuracy. Considering this, the task of choosing and preparation of datasets that can be used in the construction of such systems is important. One of the difficulties in this task is the presence of private information in the datasets, which limits their use for systems of intelligent data analysis. The paper is devoted to the development of the software system architecture for solving the classification problem based on private data. The existing methods and architectural approaches for privacy-preserving in machine learning were considered. The architecture of the software system was proposed, the characteristic feature of which is the protection of private datasets by using of functional encryption, which allows to increase the number of datasets for training publicly available data analysis and artificial intelligence systems. The proposed architecture of the software system is based on the client-server architecture and functional encryption. The components are a classifier, a generator of encryption keys, and modules of functional encryption and decryption. Prospects for further research were discussed.

LPMSAEF: Lightweight process mining-based software architecture evaluation framework for security and performance analysis

The article discusses the need for a lightweight software architecture evaluation framework that can address practitioners' concerns. Specifically, the proposed framework uses process mining and Petri nets to analyze security and performance in software development's early and late stages. Moreover, the framework has been implemented in six case studies, and the results show that it is a feasible and effective solution that can detect security and performance issues in complex and heterogeneous architecture with less time and effort. Furthermore, the article provides a detailed explanation of the framework's features, factors, and evaluation criteria. Additionally, this article discusses the challenges associated with traditional software architecture documentation methods using Unified Modeling Language diagrams and the limitations of code alone for creating comprehensive Software Architecture models. Various methods have been developed to extract implicit Software Architecture from code artifacts, but they tend to produce code-oriented diagrams instead of Software Architecture diagrams. Therefore, to bridge the model-code gap, the article proposes a framework that considers existing Software Architecture in the source code as architectural components and focuses on Software Architecture behaviors for analyzing performance and security. The proposed framework also suggests comparing Software Architecture extracted by different Process Mining algorithms to achieve consensus on architecture descriptions, using visualizations to understand differences and similarities. Finally, the article suggests that analyzing the previous version of a system's Software Architecture can lead to improvements and deviations from planned Software Architecture can be detected using traceability approaches to aid software architects in detecting inconsistencies.

Software Implementation of Methods for Modeling the Interaction of Electromagnetic Radiation with Carbon Nanocomposites

Methods for modeling the interaction of electromagnetic radiation with a carbon nanostructured composite containing various structural elements, such as carbon fibers, nanoparticles, air gaps, and transition shells are considered. It is shown that for effective and adequate modeling of the interaction of electromagnetic radiation with a carbon nanostructured composite, it is necessary to create software due to the presence of a large set of input parameters, as well as the complexity of calculations. Functional requirements for the software are formulated, reflecting the choice of models and the presence of a convenient interactive interface. The architecture of the software that implements models of interaction of electromagnetic radiation with a carbon nanostructured composite is described, and the software implementation (class structure, methods, user interface) is considered. The developed code is based on proven physical and mathematical models, which make it possible to obtain results close to experimental data. The software architecture allows to effectively manage the modeling process, and also includes the ability to modify models and take into account new structural elements. An interactive interface for users has been developed that allows to easily manage the model parameters and analyze the results of numerical experiments.

Tools, techniques, and trends in sustainable software engineering: A critical review of current practices and future directions

The quest for sustainability has extended its reach into the realm of software engineering, prompting an exploration of tools, techniques, and emerging trends to mitigate the environmental impact of software development and operation. This review provides a critical review of current practices and future directions in sustainable software engineering. In recent years, the software industry has recognized the need to address the environmental footprint of software systems, considering factors such as energy consumption, resource utilization, and carbon emissions. Consequently, a plethora of tools and techniques have emerged to support sustainable software development processes. These range from energy-efficient programming languages and frameworks to eco-friendly software architectures and design patterns. Moreover, methodologies such as Green Software Engineering (GSE) and Sustainable Software Development (SSD) have gained traction, emphasizing the integration of sustainability considerations throughout the software development lifecycle. By adopting practices like green requirements engineering, energy-aware testing, and eco-design principles, organizations can optimize their software systems for reduced environmental impact without compromising functionality or performance. Furthermore, trends in sustainable software engineering extend beyond traditional development practices. The rise of cloud computing, edge computing, and Internet of Things (IoT) technologies presents both challenges and opportunities for sustainability. Techniques such as serverless computing and containerization offer potential benefits in terms of resource efficiency and scalability, while also introducing new considerations regarding data center energy consumption and electronic waste management. Looking ahead, the future of sustainable software engineering is marked by innovation and collaboration. Emerging technologies such as artificial intelligence (AI) and blockchain hold promise for optimizing resource allocation, enhancing energy efficiency, and fostering transparency in sustainability efforts. Additionally, interdisciplinary collaboration between software engineers, environmental scientists, and policymakers will be essential in shaping a more sustainable digital ecosystem. The journey towards sustainable software engineering involves a multifaceted approach encompassing tools, techniques, and ongoing adaptation to evolving trends. By critically evaluating current practices and embracing future directions, the software industry can contribute to a more environmentally responsible and resilient future.

An advanced multimodal driver-assistance prototype for emergency-vehicle detection

In the automotive industry, intelligent monitoring systems for advanced human-vehicle interaction aimed at enhancing the safety of drivers and passengers represent a rapidly growing area of research. Safe driving behavior relies on the driver’s awareness of the road context, enabling them to make appropriate decisions and act consistently in anomalous circumstances. A potentially dangerous situation can arise when an emergency vehicle rapidly approaches with sirens blaring. In such cases, it is crucial for the driver to perform the correct maneuvers to prioritize the emergency vehicle. For this purpose, an Advanced Driver Assistance System (ADAS) can provide timely alerts to the driver about an approaching emergency vehicle. In this work, we present a driver-assistance prototype that leverages multimodal information from an integrated audio and video monitoring system. In the initial stage, sound analysis technologies based on computational audio processing are employed to recognize the proximity of an emergency vehicle based on the sound of its siren. When such an event occurs, an in-vehicle monitoring system is activated, analyzing the driver’s facial patterns using deep-learning-based algorithms to assess their awareness. This work illustrates the design of such a prototype, presenting the hardware technologies, the software architecture, and the deep-learning algorithms for audio and video data analysis that make the driver-assistance prototype operational in a commercial car. At this initial experimental stage, the algorithms for analyzing the audio and video data have yielded promising results. The area under the precision-recall curve for siren identification stands at 0.92, while the accuracy in evaluating driver gaze orientation reaches 0.97. In conclusion, engaging in research within this field has the potential to significantly improve road safety by increasing driver awareness and facilitating timely and well-informed reactions to crucial situations. This could substantially reduce risks and ultimately protect lives on the road.

Design of a robotic system to assist in the treatment of severe COVID‐19 patients

AbstractThe article presents the conceptualization, development, and implementation of a sophisticated mobile robotic system with the purpose of providing aid in the medical care of those afflicted with severe cases of COVID‐19. The robotic system will engage in verbal communication with the patient and provide updates regarding the external environment. Additionally, it will facilitate the delivery of food, beverages, and other consumable items to the isolation room. The robot has the capability to navigate to its intended location using two distinct modes: autonomous mode and online control mode. The hardware is constructed within a mobile robot system that is interconnected to the Internet over a 4G mobile network. The system employs a client–server software architecture wherein the transmission of data between the client and the server occurs through various transport protocols. Experimental simulations were conducted in an active treatment room to evaluate the performance of autonomous operating mechanisms, including obstacle avoidance positioning, safe destination navigation, and feedback display for remote robot operation.

The engine mission simulation system: coupled simulation of aircraft and engine in the mission

AbstractWhen designing future aircraft, the entire system including airframe, propulsion system, energy management and mission control must be considered in a coupled approach at an early design stage. To model and study this complex interaction, the Engine Mission Simulation System (EMSS) environment was created in cooperation with the Bundeswehr Technical Center for Aircraft and Aircraft Equipment. EMSS is intended to serve as a digital, flying test bed at the Institute of Jet Propulsion for the rapid and low-cost evaluation of new concepts for propulsion and power supply systems for new and legacy aircraft designs. This tool chain allows a detailed engine simulation under consideration of its flight condition while using an external propulsion and power control system. First, the software architecture of EMSS is discussed, which involves a propulsion simulation in NPSS® coupled with the X-Plane 11 flight simulator via MATLAB®/Simulink®. The aircraft itself is modeled as a six degrees of freedom simulation using the blade element theory, allowing both complex flight maneuvers and unusual aircraft to be easily simulated. The EMSS achieves real-time capability and enables user-friendly pre-design as well as quick trend detection through the ability to perform focused parametric studies. To evaluate the accuracy of the system’s results, the engine model used is validated against experimental data. Subsequently, the aerodynamic characteristics of the aircraft model are verified with a CFD simulation. Finally, a parametric study is used to demonstrate the mission as well as propulsion evaluation capabilities of the Engine Mission Simulation System.

Tri-Objective Vehicle Routing Problem to Optimize the Distribution Process of Sustainable Local E-Commerce Platforms

The dramatic growth of online shopping worldwide in the last few years generated negative consequences for local small retailers who do not adopt information technologies. Furthermore, the e-commerce sector is considered a good opportunity to develop sustainable logistic processes. To reach this goal, the proposed paper presents a mathematical model and a metaheuristic algorithm to solve a multi-objective capacitated vehicle routing problem (CVRP) distinguished by economic, green, and ethical objective functions. The proposed algorithm is a multi-objective simulated annealing (MOSA) that is implemented in a software architecture and validated with real-world instances that differ for the product type delivered and the geographic distribution of customers. The main result of each test is a tri-dimensional Pareto front, i.e., a decision-support system for practitioners in selecting the best solution according to their needs. From these fronts, it can be observed that if the economic and environmental performances slightly deteriorate by 1.6% and 4.5%, respectively, the social one improves by 19.4%. Furthermore, the developed MOSA shows that the environmental and social objective functions depend on the product dimensions and the geographic distribution of customers. Regarding the former aspect, this paper reports that, counter-intuitively, the metabolic energy consumption per driver decreases with bigger products because the number of necessary vehicles (and drivers) increases, and, thus, the workload is divided among more employees. Regarding the geographic distribution, this manuscript illustrates that, despite similar traveled distances, highly variable altitudes cause more carbon emissions compared to flat distributions. Finally, this contribution shows that delivering small goods decreases the distance that vehicles travel empty by 59%, with a consequent cost reduction of 16%.

Comprehensive Survey of Cutting-Edge Methods for Software Architecture Evaluation

The crucial responsibility of assessing software architecture is of utmost importance in ensuring that a software system conforms to superior qualities. It is a crucial tool for cutting expenses and labor during the course of the software development lifecycle. The main goal of software architecture evaluation is to provide reliable methods for determining and improving the quality characteristics that are innate in software. This study is deeply devoted to investigating the wide range of techniques used in software architecture assessment. One of the main focuses of these evaluation techniques is scenario-based assessments, which offer a comprehensive picture of the software's behavior under different circumstances. Within the scope of this study, a thorough analysis is carried out on eighteen different methods. Thirteen of these fall into the category of early evaluation techniques, which are positioned to detect and address architectural problems at the outset of development. The other five strategies are classified as late assessment techniques and focus on validating and optimizing the software architecture in the latter stages of the development process.