Rapid Software Development Research Articles

DevSecOps in AWS: Embedding security into the heart of DevOps practices

In today's digital landscape, rapid software development and deployment are critical for organizational success. However, security concerns have become a significant challenge in the DevOps environment. DevSecOps, which integrates security practices within the DevOps workflow, has emerged as a solution to address this gap. This paper focuses on the implementation of DevSecOps in AWS, emphasizing how security can be embedded into DevOps processes. The study explores methodologies used to integrate security within cloud-based applications, highlights the challenges and benefits of adopting DevSecOps in AWS, and provides recommendations for improving security integration in development processes.

An adaptive online monitoring system using NFSOGI-PLL for three-phase voltage unbalance in grids

The extensive utilization of unbalanced and nonlinear loads has significantly impacted power quality in modern grids. Among various metrics, the three-phase voltage unbalance factor (TPVUF) stands out as a crucial indicator. To mitigate the challenges posed by harmonics and DC components that interfere with accurate TPVUF measurements, this paper introduces the Notch Filter-based Second-Order Generalized Integrator Phase-Locked Loop (NFSOGI-PLL) for the first time and designs an adaptive online monitoring system for TPVUF based on NFSOGI-PLL. To validate its performance, the hardware design and rapid software development of the NFSOGI-PLL-based TPVUF online monitoring system are thoroughly implemented, and the system is tested under various conditions. The results indicate that the proposed system not only provides real-time performance and high accuracy, complying with the rigorous standards set by GB/T 15543-2008 and IEC 61000-4-27, but also demonstrates remarkable stability under diverse influences. These findings underscore the exceptional filtering and tracking abilities of the NFSOGI-PLL in power systems, as well as the accuracy and anti-interference capabilities of the NFSOGI-based TPVUF online monitoring system, which holds great potential for widespread application in power system control and research.

Research on the qualification of TQL-5 COTS Tools in airborne software reliability verification process based on DO-330

Abstract The rapid development of airborne software is inseparable from the help of tools, especially the TQL-5 (Tool Qualification Level 5 based on DO-330) COTS (commercial off-the-shelf tools) tool, which is the most widely used. It is worth noting that to ensure software reliability and safety, the tool also needs to be qualified. Based on the DO-330 standard, this paper introduces the qualification methods for COTS tools, TQL-5 tools, and TQL-5 COTS tools, focusing on how to qualify TQL-5 COTS tools and the objectives that tool developers and users need to meet. It plays a guiding role in the airworthiness of airborne software tool users and tool developers.

Evolving Paradigms in Automated Program Repair: Taxonomy, Challenges, and Opportunities

With the rapid development and large-scale popularity of program software, modern society increasingly relies on software systems. However, the problems exposed by software have also come to the fore. The software bug has become an important factor troubling developers. In this context, Automated Program Repair (APR) techniques have emerged, aiming to automatically fix software bug problems and reduce manual debugging work. In particular, benefiting from the advances in deep learning, numerous learning-based APR techniques have emerged in recent years, which also bring new opportunities for APR research. To give researchers a quick overview of APR techniques’ complete development and future opportunities, we review the evolution of APR techniques and discuss in depth the latest advances in APR research. In this article, the development of APR techniques is introduced in terms of four different patch generation schemes: search-based, constraint-based, template-based, and learning-based. Moreover, we propose a uniform set of criteria to review and compare each APR tool and then discuss the current state of APR development. Finally, we analyze current challenges and future directions, especially highlighting the critical opportunities that large language models bring to APR research.

Rancang Bangun Sistem Informasi Pelayanan Kesehatan Berbasis Website Pada Salvio Medical Information

In an era of rapid advances in Information Technology, health is an important aspect of human life. Clinics and hospitals compete to meet patient expectations, but often patients struggle to find suitable services, wasting valuable time. A common problem faced by many visitors to Bali is the confusion of finding a hospital or clinic that suits their needs. Salvio Medical Information, as a healthcare institution in Bali, faces similar challenges with a lack of a comprehensive information system. This can result in errors in data management, difficulties in accessing information, as well as delays in service to guests who need health care. Therefore, this research aims to design a website-based healthcare information system for Salvio Medical Information. The development approach uses the Extreme Programming model to enable rapid software development. Thus, this research is expected to make a significant contribution to efforts to develop health services that are more efficient and able to better meet the needs of patients. The expected result is a web-based health service information system that is built using the PHP programming language with the help of the Laravel framework and the extreme programming method. Where in the system built custemer can place orders through the website and the admin can manage service content and partner content on the website.

Evaluating Programming Resources: The Impact of Code Generators in Software Development

The increasing demand for rapid software development has led to the growing use of code generators, which significantly accelerate the programming process. This study investigates the impact of code generators on programming resource needs by comparing the time required by programmers of varying skill levels to develop applications using three code generators PHPMaker, PHPRunner, and CakePH versus manual coding with Laravel. Results indicate that code generators allow programmers, regardless of experience, to produce applications more quickly than manual methods. Interestingly, even novice programmers using code generators outperform senior programmers coding manually. This research contributes to the field by providing a clearer understanding of the efficiency gains offered by code generators and suggesting their potential to optimize programming resources in software development. However, the study also highlights the need for future research to evaluate additional factors, such as application complexity and quality, to further refine resource estimation models like SLIM and COCOMO when integrating code generators into the software development process. Keywords: Code Generator, programming resource, software development

Rancang Bangun Aplikasi Frontend Geographic Information System Menggunakan Metode Rad (Rapid Application Development)

North Sumatra Province has the fourth largest population in Indonesia after the Provinces of West Java, East Java, and Central Java. In 2022, the population of North Sumatra will reach 15,372,437 people. This means that North Sumatra Province has many vehicles, one of which is motorized vehicles. This makes the community do a lot of services related to motor vehicle tax at Samsat Outlets. Ease of information about the locations of Samsat Outlets is also a mandatory need for the community. The use of internet technology to develop geographic information systems is expected to provide convenience for the public in obtaining information on the location of Samsat Outlets. This system utilizes Google Maps to process and visualize the location of Samsat Outlets. The system is designed using the Rapid Application Development software development method. It is hoped that the public will more easily obtain information about the location of Samsat

Exploring factors affecting higher education students' use of Instagram for educational purposes with a structural model

The rapid development of digital software and technologies has resulted in the design of new social networks (SNS). These social network tools have added innovations to existing social media environments and made them user-friendly. Due to the integration of software technologies into all areas of life, social media platforms have become widely used especially by higher education students. Although SNSs such as YouTube and Instagram are primarily associated with entertainment, they now frequently include educational videos and posts. This study investigates the factors affecting higher education students' use of Instagram for educational purposes using a proposed structural model. The study started by developing a research model based on the literature. A data collection tool was designed based on the model and data were collected online through a link. The proposed research model and its relationships were tested using partial least squares structural equation modelling (PLS-SEM). The results of the analyses revealed that the perceived usefulness of Instagram use increases with content richness, video quality and source credibility. Furthermore, user satisfaction is positively related to perceived usefulness, leading to an increase in Instagram usage intensity.

A Review of the Interrelationships between Painting, Photography, Facial Recognition, and Artificial Intelligence Technologies in Portraiture Aesthetics

We see faces every day, and all of them leave us with different impressions. Our brains also respond emotionally to new and familiar faces we find in non-animated objects, paintings, and sculptures. To retain such memory of a face or express our feelings, we create portraits. Portraits have fascinated us for millennia. This paper reviews the interrelationships between painting, photography, facial recognition, and artificial intelligence technologies in portraiture aesthetics. The importance of portraits as a subject in artistic creation, studies, and research has led to various advancements in technological innovations. The inevitable role that portraits play in different mediums of art, history of art, communication, and security marks the intersection between humanity and identity, art and technology, as well as its undeniable position within the genre of art. Today the rapid development of digital tools, mobile software, and artificial intelligence allows not only the artist and designer to create portraitures but is also widely used by the public in all walks of life to create portraitures instantly. Driven by the marriage and momentum of art and technology in the field of new media art, will artificial intelligence and modern facial recognition technology take over the role of artists? Keywords: portrait, painting, photography, facial recognition technology, artificial intelligence

Optimizing spare part monitoring: Innovative dashboard system design for commanditaire vennotschaap using rapid application development

This research focuses on digital transformation at the Try Jaya Mobil workshop, which relies on manual processes for recording spare parts sales transactions and generating financial reports. This manual process causes various challenges, such as mismatches between incoming data and orders and a lack of historical sales records that hinder data search and analysis. The absence of a computerized system also reduces stock management and customer service efficiency. This research uses the Rapid Application Development (RAD) method to design a more sophisticated spare parts monitoring information system. The Rapid Application Development approach enables iterative and rapid software development, involving users at every stage. The information system is designed to improve accuracy, speed, and operational efficiency and enable better stock recording and monitoring. The results show that implementing a RAD-based information system can significantly improve customer service and Try Jaya Mobil's competitiveness in the market. Evaluation of the system after implementation showed improvements in operational efficiency, data accuracy, and user satisfaction. With this digital transformation, Try Jaya Mobil is expected to optimize its services and strengthen its competitive automotive industry position.

Managing Cyber Security Debt: Strategies for Identification, Prioritisation, and Mitigation

This paper explores cyber security debt, a technical debt arising from unaddressed security vulnerabilities in an organisation's IT systems. These vulnerabilities accumulate due to resource limitations, time constraints, and expertise gaps, potentially leading to security breaches and data compromises. The paper outlines the cyber security debt management process involving identification, prioritisation, and mitigation strategies. Drawing parallels to financial debt, the authors emphasise the escalating risks of delaying cyber security debt repayment. The paper underscores the significance of diligent debt management in maintaining digital resilience and mitigating cyber threats. The increasing interconnectedness of systems and rapid software development has given rise to a hidden challenge known as cyber security debt. Cyber security debt is posed as a subset of technical debt, encompassing the accumulation of security vulnerabilities within an organisation's IT infrastructure and applications. Drawing a parallel between cyber security debt and its financial counterpart, the authors underscore the grave risks of deferring debt repayment. Just as financial debt accrues interest, unresolved security vulnerabilities compound over time, elevating the likelihood of breaches and data exposure. A poignant case study of the Equifax breach exemplifies the real-world consequences of neglecting security debt management. The failure to patch a well-known vulnerability led to a colossal data breach, highlighting the urgency of addressing security weaknesses promptly. Complex in nature, cyber security debt materialises when organisations fail to address vulnerabilities during various operational life cycles. These vulnerabilities might remain concealed within IT architecture, legacy code, or third-party libraries, posing a formidable challenge to detection and resolution. By understanding the parallels between financial and cyber security debt and proactively managing the latter, organisations can enhance their ability to safeguard against evolving cyber threats and maintain a robust security posture.

Developments of ex vivo cardiac electrical mapping and intelligent labeling of atrial fibrillation substrates

Cardiac three-dimensional electrophysiological labeling technology is the prerequisite and foundation of atrial fibrillation (AF) ablation surgery, and invasive labeling is the current clinical method, but there are many shortcomings such as large trauma, long procedure duration, and low success rate. In recent years, because of its non-invasive and convenient characteristics, ex vivo labeling has become a new direction for the development of electrophysiological labeling technology. With the rapid development of computer hardware and software as well as the accumulation of clinical database, the application of deep learning technology in electrocardiogram (ECG) data is becoming more extensive and has made great progress, which provides new ideas for the research of ex vivo cardiac mapping and intelligent labeling of AF substrates. This paper reviewed the research progress in the fields of ECG forward problem, ECG inverse problem, and the application of deep learning in AF labeling, discussed the problems of ex vivo intelligent labeling of AF substrates and the possible approaches to solve them, prospected the challenges and future directions for ex vivo cardiac electrophysiology labeling.

A New Model of Organizing Mass Screening Based on Stand-Alone Artificial Intelligence Used for Fluorography Image Triage

Introduction: A rapid development of artificial intelligence software, including that for the analysis of digital fluorography images, has been noted recently. Pre-registered as a medical device, this software can be used for stand-alone analysis and triage of test results, allowing radiologists to focus on pathological findings. Objective: To substantiate the possibility and efficiency of using artificial intelligence software for stand-alone analysis and triage of digital fluorography images. Materials and methods: 88,048 digital fluorograms obtained in the first quarter of 2023 were processed using the artificial intelligence software registered in the Russian Federation as a medical device and a ROC analysis of the findings was carried out. Results: We established that default software settings with the sensitivity of 90.4 % (95 % CI: 88.2–92.7) produced specificity of 75.5 % (95 % CI: 75.2–75.8) and accuracy of 75.6 % (95 % CI: 75.3–75.9). At the maximum sensitivity of 100.0 % (95 % CI: 100–100), specificity was 77.4 % (95 % CI: 74.8–80.0) and accuracy was as high as 77.9 % (95 % CI: 75.3–80.5). We have proposed a model of organizing health care which provides for stand-alone sorting of fluorography images by the software, saving normal results without their verification by a radiologist, and sending images with abnormal findings to a radiologist for diagnosis (in the future, as artificial intelligence improves, the latter will be immediately sent to a physician of the clinical specialty). Conclusions: The established optimal scenario includes the use of artificial intelligence software to identify normal findings, which examination by a radiologist is optional when the algorithm is set to maximum sensitivity. Only the findings classified as abnormal will be subject to mandatory revision. The annual economic benefit gained by practical implementation of this approach nationwide can reach 5.6 billion rubles.

A mixed method study of DevOps challenges

DevOps practices combine software development and IT (Information Technology) operations. The continuous needs for rapid but quality software development requires the adoption of high-quality DevOps tools. There is a growing number of DevOps related posts in popular online developer forum Stack Overflow (SO). While previous research analyzed SO posts related to build/release engineering, we are aware of no research that specifically focused on DevOps related discussions. This paper aims to learn the challenges developers face while using the currently available DevOps tools and techniques along with the organizational challenges in DevOps practices. We conduct an empirical study by applying topic modeling on 174K SO posts that contain DevOps discussions. We then validate and extend the empirical study findings with a survey of 21 professional DevOps practitioners. We find that: (1) There are 23 DevOps topics grouped into four categories: Cloud & CI/CD Tools, Infrastructure as Code, Container & Orchestration, and Quality Assurance. (2) The topic category ‘Cloud & CI/CD Tools’ contains the highest number of topics (10) which cover 48.6% of all questions in our dataset, followed by the category Infrastructure as Code (28.9%). (3) The file management is the most popular topic followed by Jenkins Pipeline, while infrastructural Exception Handling and Jenkins Distributed Architecture are the most difficult topics (with least accepted answers). (4) In the survey, developers mention that it requires hands-on experience before current DevOps tools can be considered easy. They raised the needs for better documentation and learning resources to learn the rapidly changing DevOps tools and techniques. Practitioners also emphasized on the formal training approach by the organizations for DevOps skill development. Architects and managers can use the findings of this research to adopt appropriate DevOps technologies, and organizations can design tool or process specific DevOps training programs.

Implementation of Agile Software Development Methodology in Software Projects

This research is a systematic literature review using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) as a method to gather literature on agile software development methodology from Google Scholar. The result of this study is a summary of 11 articles related to Agile software development. The recommendation of this study is the use of the GLUX framework. GLUX framework integrates Lean UX into Scrum to improve the sustainability of the rapid software development process. It aims to promote a user-centric mindset and collaborative UX activities during the development process using gamification techniques. GLUX is about self-reliant teams, creating a motivating environment, and fostering teamwork.

Rancang Bangun Aplikasi Pendataan Kendaraan Operasional Menggunakan Metode Prototipe

PT. HM Sampoerna Tbk is a leading tobacco company in Indonesia as well as an affiliate of the world's leading tobacco company, Philip Morris International, which has many operational vehicles to support the process of distributing their products but the process of managing operational vehicles for maintenance or repair is still not optimal. Operational vehicles that are poorly maintained can cause problems with the vehicle at any time, causing large losses for the company. Operational vehicle maintenance must be carried out regularly so that the company's operational activities are not disrupted and to keep the vehicle in good condition and primed for traveling to distribute the company's products. The author develops an operational vehicle data collection application using the prototype method, namely rapid software development to present an overview of existing ideas and problems and then obtain feedback from users so that prototypes can be repaired immediately. The application design uses DFD and ERD and the results obtained from this research are applications that can provide information about the history of operational vehicle repairs, remind operational vehicle data management staff to carry out periodic maintenance.

Unmanned aerial vehicle navigation in underground structure inspection: A review

Many years after construction, a number of existing old tunnels and underground structures are deteriorating with time as evidenced by cracks, large deformations, water leakage and so forth, which usually require regular site inspections to record their structural deterioration by taking high‐pixel, high‐overlap images along miles of a tunnel network. For complex underground structures (e.g., long tunnels and large caves), unmanned aerial vehicles (UAVs) may be adaptive in acquiring images at multiple heights and angles with low operational costs. So far, UAV underground structural health monitoring has become mature for open‐air surveying with rapid developments in robotic software and hardware. However, the UAV image acquisition for underground working conditions still faces a number of key challenges. This paper aims to provide an overview of UAV navigation techniques in confined dark spaces for geotechnical engineers, geologists, drone developers and other interdisciplinary researchers & professionals in the structural health monitoring field. It specifies the challenges for UAV application in underground space, mainly including lack of Global Navigation Satellite System (GNSS) signals, poor lighting conditions, weak features and obstacle avoidance and then followed by strategic solutions. For example, in light of poor GNSS signals, the fusion of multi‐sensors (e.g., laser imaging, detection and ranging (LiDAR) and multi‐cameras) can enhance localization accuracy in low‐luminance underground conditions. To address obstacle avoidance, computer vision (CV)‐based navigation algorithms (e.g., deep reinforced learning [DRL]) enable effective navigation in complex 3D spaces, but their adaptability is limited by arithmetic power and pre‐training needs. The review of relevant previous studies concludes that further development for UAVs in underground space inspection may focus on operation in large‐scale geometric inspection environments, obstacle avoidance, features and semantic recognition.

FEATURES OF THE USE OF SCADA AND CATMAN SOFTWARE IN THE INFORMATION AND MEASUREMENT SYSTEM FOR CONDUCTING AME TESTS

The rapid development of software and hardware complexes and the analysis of modern views in the latest publications show the need to build a promising information and measurement system using the latest achievements of software products.
 One of the main requirements for AME manufacturers is the ability to listen to the problems and requests faced by customers and operators in their work, in the presence of the task of increasing functionality, reducing time, meeting the requirements of unification and economy.
 Increasingly shorter design and development times within the framework of modern AME creation programs require error-free solutions, complying with the “ready the first time” rule. In the sector of creation of the latest AME, it is necessary to take into account not only the efficiency and goals of defense facilities, but also environmental protection measures.
 High-quality, well-directed, economically justified and timely testing is of decisive importance for the implementation of the main stages of the project for the creation of the newest AME.
 The authors of the article conducted an analysis of SCADA and Catman software products and a consideration of their features of use as a component of information and measurement systems during testing of the AME.
 The conducted analysis of the features of the construction and functioning of the software products of advanced developers makes it possible to draw appropriate conclusions regarding the correctness and necessity of creating promising information and measurement systems that will be used in testing complex technical systems and their components.
 The use of an advanced software product, ease of construction, modularity and cost-effectiveness of the system will allow the entire list of measurement works to be performed by the organization’s engineering staff without the involvement of third-party programmers, thereby reducing time and costs.
 Thus, the use of promising information and measurement systems built taking into account the new developments of software and hardware products will solve the issue of reducing test time, increase quality and reliability, and significantly simplify the entire list of works performed according to test methods.

Differentiated analysis for music traffic in software defined networks: A method of deep learning

With the rapid development of software defined network, people have more and better choices for huge music network resources. However, they cannot find music traffic and services that meet their needs quickly and accurately. Deep learning technology has achieved various successes in speech signal processing and other fields. To meet the demand for music traffic, we propose an improved Apriori method for deep learning and implement it systematically. We then study differentiated analysis for music traffic systems and analyze the effectiveness of music traffic analysis by comparing the improved Apriori method with other methods. The experimental results indicate that the differentiated analysis for music traffic system using the improved Apriori method has a faster response speed and higher accuracy of differentiated user traffic; additionally, it has better practicability for differentiated analysis for music traffic.

Rapid Microbial-Counting Software Development basen on Mark R-CNN in Food Quality Analysis

Informasi keberadaan dan jumlah mikroorganisme pada suatu sampel khususnya sampel pangan menjadi sangat penting untuk menentukan kualitas suatu produk pangan. Banyak metode dilakukan untuk menghitung dan mengidentifikasi mikroorganisme dalam sampel. Salah satu yang paling umum dilakukan yaitu dengan menghitung manual jumlah koloni dalam agar cawan yang telah diinokulasi sampel dan diinkubasi. Metode tersebut membutuhkan fokus yang tinggi dan waktu yang lama oleh karena itu, penerapan Mask R-CNN dalam perhitungan koloni mikroorganisme pada sampel uji menjadi fokus utama dalam penelitian ini. Pendekatan mask-rcnn menjadi metode yang dipilih dalam melakukan segmentasi pada gambar sampel uji berupa foto koloni mikroba. Hasil pengenalan mikroorganisme dengan Mask R-CNN mengalami peningkatan kecepatan hitung yang signifikan dibanding metode perhitungan manual dengan tingkat akurasi yang masih perlu ditingkatkan. Dapat dikatakan, bahwa penggunaan Mask R-CNN dapat menjadi solusi menjanjikan dalam mengembangkan model hitung cepat koloni mikroba.