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Korada, Laxminarayana. "Low Code/No Code Application Development - Opportunity and Challenges for Enterprises." International Journal on Recent and Innovation Trends in Computing and Communication 10, no. 11 (2022): 209–18. http://dx.doi.org/10.17762/ijritcc.v10i11.11038.
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Low-code and no-code (LCNC) application development platforms signify a major shift in software creation and deployment strategies. This paper investigates the opportunities and challenges presented by LCNC platforms for enterprises. Historically, organizations have had to choose between developing custom solutions internally or purchasing off-the-shelf systems, each with its own set of advantages and drawbacks. LCNC platforms introduce a novel approach by facilitating rapid, cost-effective, and user-friendly application development with minimal coding expertise. This study explores the features of LCNC platforms, their adoption by hyperscalers, and their implications for traditional software engineering roles. It also examines the benefits and limitations of popular LCNC solutions, such as Microsoft Power Platform, and discusses their impact on industry practices. This paper concludes with a forward-looking perspective on the development of LCNC technology, underscoring its role in driving digital transformation and fostering innovation.
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Слотвицкая, А. А., Б. В. Мартынов, and Е. С. Прокопенко. "THE PROSPECTS AND EFFICIENCY OF NO-CODE AND LOW-CODE PLATFORMS FOR BUSINESS AUTOMATION." Proceedings in Cybernetics 23, no. 2 (2024): 71–75. http://dx.doi.org/10.35266/1999-7604-2024-2-9.
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In recent years, there has been a growing interest in no-code automation tools for business processes in the IT industry. Over the last fi ve years, investments in no-code platforms have crossed one billion dollars. The study focuses on the analysis of these technologies in the context of small and large businesses. However, the issue of replacing traditional development remains. The study aims to determine who benefits from using no-code and who benefi ts from traditional evelopment. The research is relevant since companies have limited resources. Methods include effi ciency analysis and comparison of implementation results. The advantages of no-code include speed, cost, and low risks, but it is dependent on the software solution and requires programming skills. The study calls for a balance between the use of no-code and traditional development to maximize benefi ts. Based on the research, it is established that no-code and low-code development are less effective without traditional programming and will be more effective for implementation in companies that already have a team of IT specialists.
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Pydde, Jan Philipp, Robin Dominic Ziegler, and Arthur Mezger. "Low-Code/No-Code erfolgreich implementieren/Successful implementation of low-code/no-code apps – Success factors for the implementation of low-code/no-code platforms in companies." wt Werkstattstechnik online 115, no. 03 (2025): 132–40. https://doi.org/10.37544/1436-4980-2025-03-14.
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Unternehmen müssen sich durch die digitale Transformation flexibel anpassen. Low Code/No Code (LCNC) bietet hierfür eine Lösung, indem es die Softwareentwicklung vereinfacht. Diese Arbeit identifiziert Erfolgsfaktoren für die Implementierung von LCNC-Lösungen in produzierenden Unternehmen. Die Literatur wird in Mensch, Technologie, Organisation und Aufgabe kategorisiert. Ein Prisma-basierter, systematischer Literaturreview dient der Analyse, um einen Leitfaden für die Implementierung von LCNC-Lösungen zu erstellen.
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Sufi, Fahim. "Algorithms in Low-Code-No-Code for Research Applications: A Practical Review." Algorithms 16, no. 2 (2023): 108. http://dx.doi.org/10.3390/a16020108.
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Algorithms have evolved from machine code to low-code-no-code (LCNC) in the past 20 years. Observing the growth of LCNC-based algorithm development, the CEO of GitHub mentioned that the future of coding is no coding at all. This paper systematically reviewed several of the recent studies using mainstream LCNC platforms to understand the area of research, the LCNC platforms used within these studies, and the features of LCNC used for solving individual research questions. We identified 23 research works using LCNC platforms, such as SetXRM, the vf-OS platform, Aure-BPM, CRISP-DM, and Microsoft Power Platform (MPP). About 61% of these existing studies resorted to MPP as their primary choice. The critical research problems solved by these research works were within the area of global news analysis, social media analysis, landslides, tornadoes, COVID-19, digitization of process, manufacturing, logistics, and software/app development. The main reasons identified for solving research problems with LCNC algorithms were as follows: (1) obtaining research data from multiple sources in complete automation; (2) generating artificial intelligence-driven insights without having to manually code them. In the course of describing this review, this paper also demonstrates a practical approach to implement a cyber-attack monitoring algorithm with the most popular LCNC platform.
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Das, Jitendra Kumar. "Low-code/No-code Development Empowering Non-Developers: A Study on the Rise of Low-Code Web Platforms." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 6695–98. https://doi.org/10.22214/ijraset.2025.71770.
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Abstract: The rapid evolution of digital technologies has catalyzed a significant shift in software development practices, paving the way for Low-Code and No-Code (LCNC) platforms that empower non-developers to participate in application creation. This study explores the growing adoption of LCNC web platforms, examining how they enable individuals without formal programming skills to build functional, scalable web applications. Through a mixed-methods approach involving case studies, platform analysis, and user interviews, the research identifies key drivers behind the rise of LCNC tools, such as reduced development time, lower costs, and enhanced accessibility. The paper also investigates the broader implications for organizations, including shifts in workforce dynamics, the democratization of innovation, and challenges related to scalability and governance. Ultimately, this study highlights the transformative potential of LCNC development in bridging the gap between technical and non-technical users, fostering a more inclusive digital innovation ecosystem.
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Sandhya, Rani Koppanathi. "Low-Code/No-Code Tools for Salesforce Integration Development." Journal of Scientific and Engineering Research 8, no. 6 (2021): 197–205. https://doi.org/10.5281/zenodo.13753044.
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Over the last couple of years, low-code/no-code development is gaining increased interest for its potential to speed up application creation with less direct coding. In specific, these platforms have experienced high value for merging advanced Customer Relationship Management (CRM) systems such as Salesforce that generally involve flawless communication with many third-party apps. This paper explores the use of Low-code no code tools for Salesforce Integration/Development, their features and advantages as well as caveats. This study aims to provide insights into how Low-code no code tools can actually help in improving Salesforce integration irrespective of whether the user has technical skills or not using various set of platforms available as of today. The results point to Low-code no code tools offering many benefits in terms of speed and ease of use, but also some limitations especially regarding complex integrations. The paper concludes with recommending future research and developments in this area.
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Balaji Bodicherla. "The Rise of Low-Code/No-Code Development: Democratizing Application Development." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 2 (2025): 171–78. https://doi.org/10.32628/cseit251112398.
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The emergence of low-code and no-code development platforms has fundamentally transformed the software development landscape, offering organizations innovative approaches to application development. These platforms have significantly impacted various sectors, from large enterprises to small and medium-sized businesses, particularly in accelerating digital transformation initiatives. Adopting these platforms has shown remarkable benefits in terms of development efficiency, cost reduction, and business agility while presenting important considerations regarding governance, security, and technical limitations. As organizations increasingly embrace these technologies, the market has shown substantial growth, driven by the demand for rapid application development and business process automation, with cloud-based deployments becoming the preferred choice for implementation.
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ИВАНОВ, Ф. Д., and М. О. ПЕТРАКОВ. "ANALYSIS OF NO-CODE AND LOW-CODE PLATFORMS AS A TOOL TO ACCELERATE THE DIGITAL TRANSFORMATION PROCESSES OF LARGE COMPANIES." Экономика и предпринимательство, no. 7(156) (September 20, 2023): 1240–47. http://dx.doi.org/10.34925/eip.2023.156.7.223.
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В статье представлены результаты анализа no-code и low-code платформ в качестве инструмента ускорения процессов цифровой трансформации крупных компаний. Объектом данного исследования является инструменты программирования низкого и нулевого кода. Предметом исследования является воздействие инструментов низкого и нулевого кода на темп цифровой трансформации. The article presents the results of the analysis of no-code and low-code platforms as a tool for accelerating the digital transformation processes of large companies. The object of this study is low and zero code programming tools. The subject of the study is the impact of low and zero code tools on the pace of digital transformation.
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Пальмов, С. В., М. П. Абашин та Н. А. Гулынин. "Low-code и no-code платформы в Российской Федерации". Innovative economy: information, analytics, forecasts, № 6 (16 грудня 2024): 107–14. https://doi.org/10.47576/2949-1894.2024.6.6.015.
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В статье рассматриваются преимущества и недостатки российских low-code и no-code платформ. На современном рынке подобных платформ представлено большое количество отраслевых решений от различных разработчиков, таких как «ELMA365», «BPMSoft», НПЦ «БизнесАвтоматика», «Directum» и т. д. Главными преимуществами от использования low-code и no-code систем являются скорость внедрения и настройки, стоимость содержания. В качестве недостатков, выделенных представителями бизнеса, можно выделить недостаточную гибкость, ограничения в области безопасности и недостаток функциональных возможностей. This paper examines the advantages and limitations of Russian low-code and no-code platforms. The modern market offers numerous industry-specific solutions developed by companies such as ELMA365, BPMSoft, NPC Business Automation, and Directum, among others. Key benefits of adopting low-code and no-code systems include rapid deployment, ease of customization, and cost efficiency. However, business users highlight certain drawbacks, including limited flexibility, security constraints, and insufficient functional capabilities.
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Praveen Kumar Chakilam. "Democratizing enterprise integration: The emergence of low-code/no-code integration platforms." World Journal of Advanced Engineering Technology and Sciences 15, no. 2 (2025): 008–14. https://doi.org/10.30574/wjaets.2025.15.2.0492.
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Low-code/no-code (LC/NC) integration platforms are fundamentally transforming enterprise connectivity by democratizing integration capabilities previously restricted to specialized technical personnel. These platforms employ intuitive visual interfaces, pre-built connectors, and intelligent automation to abstract away technical complexity, enabling both business users and IT professionals to collaborate on integration solutions. The global market for these technologies is experiencing remarkable growth, projected to reach USD 13.7 billion by 2027 at 25.1% CAGR, reflecting their strategic importance. Organizations implementing low-code/no-code (LC/NC) integration solutions report dramatic improvements in development timelines, with projects completed up to 10 times faster than traditional approaches. This acceleration drives operational efficiencies across sectors, including healthcare, financial services, retail, and manufacturing, each benefiting from industry-specific integration capabilities. Despite compelling advantages, including enhanced businessIT collaboration, reduced operational costs, and increased process innovation, organizations must navigate challenges related to technical limitations, governance complexity, and potential vendor lock-in. By understanding both the transformative potential and inherent limitations of these platforms, organizations can develop effective implementation strategies that balance accessibility with enterprise-grade performance requirements.
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Researcher. "DEMOCRATIZING DATA INSIGHTS: THE IMPACT OF NO-CODE/LOW-CODE PLATFORMS ON BUSINESS INTELLIGENCE VISUALIZATION." International Journal of Research In Computer Applications and Information Technology (IJRCAIT) 7, no. 2 (2024): 647–61. https://doi.org/10.5281/zenodo.14025139.
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This article examines the transformative impact of no-code and low-code platforms on data visualization practices in contemporary business environments. As organizations grapple with the increasing complexity and volume of data, these platforms emerge as powerful tools for democratizing data access and empowering non-technical users to create sophisticated visualizations and dashboards. Through a comprehensive analysis of current literature, industry reports, and case studies, we explore how these platforms are reshaping traditional data visualization workflows, enhancing collaboration between technical and non-technical teams, and fostering a culture of data-driven decision-making across organizational hierarchies. Our findings suggest that while no-code/low-code platforms offer significant benefits in terms of agility, cost-effectiveness, and user empowerment, they also present challenges related to data governance, scalability, and integration with existing systems. This article contributes to the growing body of knowledge on data democratization and provides practical insights for organizations seeking to leverage no-code/low-code solutions to enhance their data visualization capabilities and drive innovation.
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Shridhar, Shreyas. "Analysis of Low Code-No Code Development Platforms in comparison with Traditional Development Methodologies." International Journal for Research in Applied Science and Engineering Technology 9, no. 12 (2021): 508–13. http://dx.doi.org/10.22214/ijraset.2021.39328.
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Abstract: This paper examines the overview of low-code/no-code development platforms in comparison with traditional development methodologies and examines the benefits and limitations of the same. For several decades, businesses have had multiple options when they demanded new information systems. They could develop a new system using in-house developers, or they could order a system from an external merchant. This offers a close fit to business obligations. However, nowadays, there is a new alternative that is becoming increasingly prevalent. Low code/no code (LC/NC) applications can cater to business requirements efficiently, can be implemented instantly, and the cost is much less than systems developed in-house. Few, if any, programming skills are required. Keywords: Traditional development, No code development, low code development, Low code No code development, Software development life cycle (SDLC)
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Kolawole Joseph Ajiboye. "The role of Low-Code/No-Code platforms in accelerating digital transformation in regulated industries." International Journal of Science and Research Archive 4, no. 1 (2021): 262–79. https://doi.org/10.30574/ijsra.2021.4.1.0159.
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The modern digital age transforms regulated business operations and supports operational efficiency while promoting innovation together with regulatory compliance. The quick changes in regulatory environments pose challenges to traditional development methods because they fail to maintain proper speed. To speed up transformation processes low-code/no-code (LCNC) platforms offer organizations tools that help them create applications without significant coding requirements. The technology enables business personnel to gain control while providing workflow improvement together with less dependence on IT teams which results in better agility and faster response times. LCNC platforms bring limitations when used for highly customized enterprise solutions and pose governance complexities to users who also must address security concerns. Any organization needs to find an equilibrium between simple user experience regulatory adherence and powerful system security to reach its full potential. This paper evaluates how Low-Code No-Code platforms drive digital transformation within regulated industries through assessments of their capabilities to link operational objectives with technical infrastructure. The adoption of LCNC costs less during development and reduces project deployment periods yet it requires perfect industry guidelines implementation to succeed. LCNC platforms establish themselves as advanced solutions during digital transformation if they receive proper strategic integration although deploying them demands meticulous planning for risk reduction and extended value optimization.
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Kacheru, Goutham, Nagaraju Arthan, and Rohit Bajjuru. "Artificial Intelligence (AI) for Low-Code and No-Code Development: Making Non-Developers Developers in 2024." Formosa Journal of Multidisciplinary Research 4, no. 1 (2025): 141–50. https://doi.org/10.55927/fjmr.v4i1.13369.
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Low-code and no-code development platforms are here to transform the software development landscape by allowing even non-technical users build applications without the need of their advanced programming skills. Artificial Intelligence (AI) is the most crucial player in this evolution; reinvigorating these platforms with intelligent automation, device responsive templates and user-friendly interfaces (2024). Users can design, build, and deploy applications easily with AI-powered features (e.g., Natural Language Processing (NLP), drag-and-drop functionality to-design application & code-generation tools). Democratization of Application Development These innovations democratize application development, thereby allowing businesses to innovate faster, lessen the reliance on professional developers, and meet the surging demand for digital solutions. In this paper, we look at how AI-assisted low-code and no-code platforms are changing the way new apps are being developed, empowering non-developers to participate in software creation and accelerating automation of app development. It also presents the challenges and future aspects that we have to deal with in order to use AI on these platforms, as well as their future role of building a bridge between technical expertise and creative problem-solving.
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Firoz Mohammed Ozman. "A systematic literature review on current developments of low code-no code solutions in the IT sector." World Journal of Advanced Engineering Technology and Sciences 14, no. 3 (2025): 162–69. https://doi.org/10.30574/wjaets.2025.14.3.0072.
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The growing scarcity of skilled software developers has prompted organizations to turn to low-code/no-code (LCNC) platforms, which allow non-technical users to develop applications without requiring extensive knowledge of coding. LCNC platforms use AI and ML to automate the development process, thereby encouraging innovation and collaboration between IT and business teams. These platforms offer a plethora of benefits-including reduced times for development with drawbacks like vendor lock-in, higher security risks, and less competence in dealing with complex applications. Such research investigates business process changes facilitated by LCNC platforms in pursuit of filling knowledge gaps regarding the way they support improving organizational performance and leading innovation. A systematic review of the existing literature shows both developing trends and obstacles in the adaptation of LCNC platforms in the IT sector. According to findings, these platforms incorporate the entire process of software development, which makes collaboration better and highly decreases the project timelines for organizations, providing them with a window opportunity to enhance efficiency and innovation in their operations. However, organizations need to address governance, security concerns, and scalability issues for the optimal integration of LCNC. Some practical recommendations are to set up a Center of Excellence (CoE), hybrid development approaches, and workforce training programs. This research enriches both academic and practical knowledge of LCNC technologies, enabling IT professionals and organizations to lead digital transformation and maintain competitive advantage in a dynamic market environment.
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Naqvi, Bilal, Damian Kedziora, Lanqi Zhang, and Shola Oyedeji. "Quality of Low-Code/No-Code Development Platforms Through the Lens of ISO 25010:2023." Computer 58, no. 3 (2025): 30–40. https://doi.org/10.1109/mc.2024.3493192.
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Domański, Roman, Hubert Wojciechowski, Jacek Lewandowicz, and Łukasz Hadaś. "Digitalization of Management Processes in Small and Medium-Sized Enterprises—An Overview of Low-Code and No-Code Platforms." Applied Sciences 13, no. 24 (2023): 13078. http://dx.doi.org/10.3390/app132413078.
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The permanent digitization of management processes entails, among other things, a need for the automation of the process of making certain business decisions. The aim of the article is to review and evaluate low-code/no-code platforms used, for instance, in small and medium-sized enterprises, available on the Polish IT market. Using a systematic literature review, an assessment of the scale of the discussed issue, involving the number of publications, detailed topics covered, etc., is provided in the theoretical part of the study. During our research, using grey incidence analysis, a ranking of low-code/no-code platforms is created based on the characteristics that they offer. The article highlights the benefits of using new technologies in the form of low-code/no-code platforms in the management of smaller organizations.
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Lebens, Mary, Roger J Finnegan, Steven C Sorsen, and Jinal Shah. "Rise of the Citizen Developer." Muma Business Review 5 (2021): 101–11. http://dx.doi.org/10.28945/4885.
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A worldwide shortage of developers has made low- and no-code platforms important and necessary. This paper investigates the use of these platforms in organizations, along with the role of workforce automation tools. A survey was conducted to find out how prevalent low- and no-code platforms and workforce automation tools are within companies. These platforms are used by citizen developers, employees who are working outside of the Information Technology (IT) department and are not professional programmers. With low- and no-code platforms citizen developers can create the applications that are needed by their work units or even their entire organizations. These platforms are seen as key to the demands of digital transformation. The results of this study are that companies both large and small are making use of low- and no-code platforms, as well as workforce automation tools. In addition, the majority of organizations have employees outside of the IT department who are creating technology solutions. The broad implication of this research is that citizen developers using low- and no-code platforms to create technology solutions may be the solution to the current shortage of developers. By using low- and no-code platforms, the citizen developer can create the applications that the manager needs for their team. This increases the technology available to the organization while at the same time reducing the pressure on the IT department.
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Jasman, Jasman. "The Impact of Low-Code and No-Code Development on IT Workforces and Software Engineering Practices in Indonesia." West Science Information System and Technology 2, no. 03 (2024): 413–18. https://doi.org/10.58812/wsist.v2i03.1815.
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This study examines the impact of low-code and no-code (LCNC) development platforms on IT workforces and software engineering practices in Indonesia. Employing a quantitative approach with 50 respondents and data analysis using SPSS version 25, the research investigates the relationships between LCNC adoption and variables such as workforce productivity, skill adaptability, software quality, and development efficiency. The findings indicate that LCNC platforms significantly enhance workforce productivity and development efficiency, with moderate impacts on skill adaptability and mixed perceptions of software quality. These results suggest that LCNC platforms have the potential to revolutionize software development processes in Indonesia, provided that challenges related to skill adaptation and quality assurance are effectively addressed.
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Sodano, J. T., and Joanna F. DeFranco. "Citizen Development, Low-Code/No-Code Platforms, and the Evolution of Generative AI in Software Development." Computer 58, no. 5 (2025): 101–4. https://doi.org/10.1109/mc.2025.3547073.
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Minaya Vera, Cristhian Gustavo, Mendoza Velez Oswaldo Vicente, Irina Loreley Arias Vera, Minaya Vera Andrés Alexander, and Henry Fabricio Bravo Vera. "Low/No-code development platforms and the future of software developers." Minerva 1, Special (2022): 21–33. http://dx.doi.org/10.47460/minerva.v1ispecial.76.
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Low/No-code is a trend in the software development industry that seeks to provide those without specific computer training with easy-to-use tools to create applications or programs to meet a particular business need. In the market, multiple platforms allow users to develop software solutions withsome code or, in some cases, no need for coding. This paper explores the origins of this trend and how it has evolved, and its adoption in software development. The investigation also analyzed the implications of this trend for software professionals over the near future.
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Kulkarni, Mayuresh. "Deciphering Low-Code/No-Code Hype – Study of Trends, Overview of Platforms, and Rapid Application Development Suitability." International Journal of Scientific and Research Publications (IJSRP) 11, no. 7 (2021): 536–40. http://dx.doi.org/10.29322/ijsrp.11.07.2021.p11570.
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Samruddhi, Bhabad. "From Code to No-Code Tools: The Evolution of How We Build. NOVEMBER-2024." ENTECH 2, no. 11 (2024): 12–14. https://doi.org/10.5281/zenodo.14511949.
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Once upon a time, <strong>software development</strong> was a domain reserved for <strong>coding wizards</strong> who could conjure up magic with lines of code. Fast-forward a few decades, and the landscape of tech creation has transformed dramatically. Today, we’ve arrived at a point where even non-coders can build fully functional applications, thanks to low-code and no-code tools & platforms. But how did we get here? What does this evolution mean for the <strong>future of technology?</strong>Let’s embark on a journey to understand the transition from traditional coding to low-coding and no-code development, exploring its impact on innovation, accessibility, and careers.
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Villegas-Ch., William, Joselin García-Ortiz, and Santiago Sánchez-Viteri. "Identification of the Factors That Influence University Learning with Low-Code/No-Code Artificial Intelligence Techniques." Electronics 10, no. 10 (2021): 1192. http://dx.doi.org/10.3390/electronics10101192.
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Education is one of the sectors that improves the future of societies; unfortunately, the pandemic generated by coronavirus disease 2019 has caused a variety of problems that directly affect learning. Universities have found it necessary to begin a transition towards remote or online educational models. To do so, the only method that guarantees the continuity of classes is using information and communication technologies. The transition in the foreground points to the use of technological platforms that allow interaction and the development of classes through synchronous sessions. In this way, it has been possible to continue developing both administrative and academic activities. However, in effective education, there are factors that create an ideal environment where the generation of knowledge is possible. By moving from traditional educational models to remote models, this environment has been disrupted, significantly affecting student learning. Identifying the factors that influence academic performance has become the priority of universities. This work proposes the use of intelligent techniques that allow the identification of the factors that affect learning and allow effective decision-making that allows improving the educational model.
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Mallika Rao, Basaveni Siri, and Sai Santosh Goud Bandari. "Replacing AI Agents for Backend." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–8. https://doi.org/10.55041/ijsrem.ncft011.
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Abstract—Creating modern applications using a heavy backend is a big task for developers. Front end can be created easily using scripting languages like HTML, CSS, java script, react frameworks etc. and many low code tools like WordPress, Figma, Bolt etc., but creating a fully working backend is a difficult part for developers, students or startups. Instead of writing thousands of lines of code we can build applications using AI agents. Sounds unreal right? But yes, it’s possible we can replace maximum of our backend logic using AI agents. Traditional backend development involves significant manual effort in writing, testing and maintaining code to support functionalities of backend such as authentication, database management, business logic and notifications. With emergence of AI and workflow orchestration platforms, we can see a high potential on how we can transform backend systems using these intelligent agents, with advancements in artificial intelligence and no-code orchestration platforms such as n8n, there is a drastic change where backend systems can be created, managed and evolved by AI agents. This paper explores how AI agents can transform backend development eliminating boilerplate code and introducing adaptive, scalable and intelligent architectures to design an application. Keywords—AI Agents, Backend Development, Workflow Automation, n8n, No-Code Platforms, Intelligent Systems, Application Architecture, Natural Language Processing, Low-Code Development, Large Language Models (LLMs), Orchestration Tools, Business Logic Automation, API Integration, Smart Workflows
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Sunil, Kumar V. "Next-Generation Software Engineering: A Study on AI-Augmented Development, DevSecOps and Low-Code Frameworks." Journal of Advances in Computational Intelligence Theory 7, no. 2 (2025): 5–10. https://doi.org/10.5281/zenodo.15173513.
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<em>The software engineering domain is undergoing a paradigm shift driven by the integration of Artificial Intelligence (AI), security-by-design practices like DevSecOps, and the rise of low-code/no-code development platforms. This study explores the convergence of these three transformative trends, focusing on how AI-augmented development enhances code quality and developer productivity, how DevSecOps embeds security throughout the software development lifecycle (SDLC), and how low-code platforms democratize software creation. Through an analytical synthesis of contemporary literature and industrial practices, the research identifies key benefits such as faster time-to-market, continuous delivery with built-in security, and improved collaboration between developers, testers, and operations teams. The study also addresses the challenges of AI explainability, security automation, and scalability in low-code systems. The findings suggest that the next generation of software engineering must embrace a synergistic model where AI, security, and accessibility converge to produce secure, efficient, and user-centric software at scale.</em>
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Prozorova, G. V. "Adaptable software tools for searching objects-analogues tasks in NO-CODE concept." E3S Web of Conferences 460 (2023): 04010. http://dx.doi.org/10.1051/e3sconf/202346004010.
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The paper is devoted to the problem of methodological and software support for the search of object analogues, performed when solving the problems of modelling and designing the development of oil and gas fields. The article shows that there is no single generally accepted methodology for searching analogues, existing methodologies differ in applied similarity criteria and search algorithms, are adapted to the search conditions, and are modernised. With the inconsistency of methods computer programs for searching analogues are created at a low level of abstraction, for a limited range of tasks, the existing developments are integrated with corporate databases and in general do not solve the problem of providing analysts with pro-software tools. As a solution we propose the development of programs for searching analogues in the concept of "no-code" (without programming) on the basis of analytical platforms. The "no-code" approach will allow analysts without involving programmers to create software tools for searching analogues, implementing their own variant methods. The article presents the authors' algorithm for express analysis of data at the initial stage of analogue search and the software tool that implements it, created "no code" on the basis of the Russian analytical platform Loginom.
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Prozorova, Galina V., Polina S. Skochina, Sergey N. Saranchin, and Mikhail A. Chingalaev. "Adaptable software tools for searching objects-analogues tasks in NO-CODE concept." Geoinformatika, no. 1 (March 27, 2024): 35–41. http://dx.doi.org/10.47148/1609-364x-2024-1-35-41.
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The paper is devoted to the problem of methodological and software support for the search of object analogues, performed when solving the problems of modelling and designing the development of oil and gas fields. The article shows that there is no single generally accepted methodology for searching analogues, existing methodologies differ in applied similarity criteria and search algorithms, are adapted to the search conditions, and are modernised. With the inconsistency of methods computer programs for searching analogues are created at a low level of abstraction, for a limited range of tasks, the existing developments are integrated with corporate databases and in general do not solve the problem of providing analysts with pro-software tools. As a solution we propose the development of programs for searching analogues in the concept of "no-code" (without programming) on the basis of analytical platforms. The "no-code" approach will allow analysts without involving programmers to create software tools for searching analogues, implementing their own variant methods. The article presents the authors' algorithm for express analysis of data at the initial stage of analogue search and the software tool that implements it, created "no code" on the basis of the Russian analytical platform Loginom.
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Batsaras, Christos, and Stelios Xinogalos. "A Comparative Analysis of Low or No-Code Authoring Tools for Location-Based Games." Multimodal Technologies and Interaction 7, no. 9 (2023): 86. http://dx.doi.org/10.3390/mti7090086.
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This article presents a comparative analysis of four low or no-code location-based game (LBG) authoring tools, namely Taleblazer, Aris, Actionbound, and Locatify. Each tool is examined in detail, with an emphasis on the functions and capabilities it provides for the development of LBGs. The article builds on the history and purpose of LBGs, their characteristics, as well as basic concepts and previous applications, placing emphasis both on the technological and pedagogical dimensions of these games. The evaluation of the tools is based on certain criteria, or metrics, recorded in the literature and empirical data collected through the development of prototype games for each tool. The tools are comparatively analyzed in terms of the LBG’s constituent features they incorporate, the fundamental and additional functionality provided to the developer, as well as the existence or absence of features that captivate players in the game experience. Moreover, feedback is provided based on the practical use of the platforms for developing LBGs in order to support prospective developers in making an informed choice of an LBG platform for implementing a specific game. The games were created by taking advantage of as many features of the tools as possible in order to have a more fair and complete evaluation. This study aims to highlight the affordances and limitations of the investigated low or no-code LBG authoring tools, enabling anyone interested in developing an LBG to choose the most appropriate tool taking into account their needs and technological background or designing their own LBG authoring tools.
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Gong, Eun Jeong, Chang Seok Bang, Jae Jun Lee, et al. "No-Code Platform-Based Deep-Learning Models for Prediction of Colorectal Polyp Histology from White-Light Endoscopy Images: Development and Performance Verification." Journal of Personalized Medicine 12, no. 6 (2022): 963. http://dx.doi.org/10.3390/jpm12060963.
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Background: The authors previously developed deep-learning models for the prediction of colorectal polyp histology (advanced colorectal cancer, early cancer/high-grade dysplasia, tubular adenoma with or without low-grade dysplasia, or non-neoplasm) from endoscopic images. While the model achieved 67.3% internal-test accuracy and 79.2% external-test accuracy, model development was labour-intensive and required specialised programming expertise. Moreover, the 240-image external-test dataset included only three advanced and eight early cancers, so it was difficult to generalise model performance. These limitations may be mitigated by deep-learning models developed using no-code platforms. Objective: To establish no-code platform-based deep-learning models for the prediction of colorectal polyp histology from white-light endoscopy images and compare their diagnostic performance with traditional models. Methods: The same 3828 endoscopic images used to establish previous models were used to establish new models based on no-code platforms Neuro-T, VLAD, and Create ML-Image Classifier. A prospective multicentre validation study was then conducted using 3818 novel images. The primary outcome was the accuracy of four-category prediction. Results: The model established using Neuro-T achieved the highest internal-test accuracy (75.3%, 95% confidence interval: 71.0–79.6%) and external-test accuracy (80.2%, 76.9–83.5%) but required the longest training time. In contrast, the model established using Create ML-Image Classifier required only 3 min for training and still achieved 72.7% (70.8–74.6%) external-test accuracy. Attention map analysis revealed that the imaging features used by the no-code deep-learning models were similar to those used by endoscopists during visual inspection. Conclusion: No-code deep-learning tools allow for the rapid development of models with high accuracy for predicting colorectal polyp histology.
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Chrisna, I. Dewa Ayu Indira Wulandari, Dana Sulistiyo Kusumo, and Rosa Reska Riskiana. "LOW CODE INTEGRATION TESTING IN OUTSYSTEMS PERSONAL ENVIRONMENT." Jurnal Teknik Informatika (Jutif) 5, no. 2 (2024): 551–60. https://doi.org/10.52436/1.jutif.2024.5.2.1673.
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As implied by its name, low code platforms enable software development with minimal or no coding involved. Consequently, ensuring the correctness of the software becomes crucial as developers are unable to directly scrutinize the logic. Furthermore, discussions about the various testing approaches applicable to such applications are relatively scarce. This study aims to conduct integration testing through both white box and black box methods, as well as exploring the types of testing that can be carried out on low code based applications. This research involves several stages, including creating a basic e-shop application and API using OutSystems, test preparation, and test execution. API testing utilizes OutSystems' BDDFramework and Postman automation testing tools, while web page integration is carried out using Katalon Studio. The test results indicate only one of the total 23 test cases was considered failed because the result did not match the expected result. Apart from that, of the four existing levels of testing, component testing can also be carried out on the OutSystems application. However, only with the black box testing method because testing is carried out without accessing the program source code. The comparative execution of API testing (white box) using two distinct testing tools reveals the superior effectiveness of Postman over BDDFramework, offering more comprehensive test outcomes and enhanced test case coverage. In the realm of UI integration testing, Katalon Studio emerges as a fitting tool, benefiting from its record and replay feature that facilitates the definition of test steps.
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Akhilesh Gadde. "Democratizing Software Engineering through Generative AI and Vibe Coding: The Evolution of No-Code Development." Journal of Computer Science and Technology Studies 7, no. 4 (2025): 556–72. https://doi.org/10.32996/jcsts.2025.7.4.66.
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The integration of generative artificial intelligence (AI) into software development processes represents a paradigm shift in how individuals interact with technology creation tools. This article examines the emergence of intuitive programming approaches colloquially termed "vibe coding" alongside traditional no-code and low code platforms, analyzing their combined potential to democratize software engineering practices. Through systematic analysis of current research, It identifies key technological frameworks, implementation challenges, and potential socioeconomic implications of AI-assisted development environments. The article findings suggest that generative AI fundamentally transforms the accessibility paradigm by bridging natural language expression with functional software creation, potentially reducing traditional barriers to entry while introducing new considerations regarding technical depth, sustainability, and equity in software production ecosystems.
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Brandon, Colm, Steve Boßelmann, Amandeep Singh, et al. "Cinco de Bio: A Low-Code Platform for Domain-Specific Workflows for Biomedical Imaging Research." BioMedInformatics 4, no. 3 (2024): 1865–83. http://dx.doi.org/10.3390/biomedinformatics4030102.
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Background: In biomedical imaging research, experimental biologists generate vast amounts of data that require advanced computational analysis. Breakthroughs in experimental techniques, such as multiplex immunofluorescence tissue imaging, enable detailed proteomic analysis, but most biomedical researchers lack the programming and Artificial Intelligence (AI) expertise to leverage these innovations effectively. Methods: Cinco de Bio (CdB) is a web-based, collaborative low-code/no-code modelling and execution platform designed to address this challenge. It is designed along Model-Driven Development (MDD) and Service-Orientated Architecture (SOA) to enable modularity and scalability, and it is underpinned by formal methods to ensure correctness. The pre-processing of immunofluorescence images illustrates the ease of use and ease of modelling with CdB in comparison with the current, mostly manual, approaches. Results: CdB simplifies the deployment of data processing services that may use heterogeneous technologies. User-designed models support both a collaborative and user-centred design for biologists. Domain-Specific Languages for the Application domain (A-DSLs) are supported through data and process ontologies/taxonomies. They allow biologists to effectively model workflows in the terminology of their field. Conclusions: Comparative analysis of similar platforms in the literature illustrates the superiority of CdB along a number of comparison dimensions. We are expanding the platform’s capabilities and applying it to other domains of biomedical research.
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Moulaei, Khadijeh, and Kambiz Bahaadinbeigy. "A New Revolution in Healthcare Transformation Using Hyper-Automation Technologies." Frontiers in Health Informatics 12 (April 15, 2023): 134. http://dx.doi.org/10.30699/fhi.v12i0.422.
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As someone who has been following the development of hyper-automation technologies in healthcare, I wanted to write to you about the many optimistic outcomes that these technologies have already produced. I am writing to express my excitement about many potential and benefits of hyper-automation technologies in healthcare. Hyper-automation, which includes the use of smart technologies such as artificial intelligence, low-code/no-code (LCNC) platforms, machine learning, robotics and other technologies to automate and optimize processes, has the possibility to transform healthcare in many ways [1].
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Nagasruthi Kattula. "The Evolution of CRM: AI-Powered Personalization Meets Hyperautomation." World Journal of Advanced Engineering Technology and Sciences 15, no. 1 (2025): 1090–105. https://doi.org/10.30574/wjaets.2025.15.1.0317.
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The evolution of Customer Relationship Management (CRM) has transcended traditional tracking systems to embrace sophisticated AI-powered personalization and hyperautomation technologies. This technological convergence addresses fundamental limitations of legacy CRM platforms, which struggle with data silos, emotional engagement, rigid workflows, and batch processing models. Modern cloud-based CRM systems leverage Customer Data Platforms to create comprehensive customer profiles, while generative AI transforms communication strategies through contextually aware content creation. Hyperautomation extends these capabilities by integrating Robotic Process Automation, AI-enhanced decision making, and low-code/no-code platforms to optimize end-to-end processes. Supporting these advances, multi-cloud architectures and edge computing provide the infrastructure necessary for real-time personalization at scale. Organizations implementing these technologies report substantial improvements in customer retention, revenue growth, operational efficiency, and scalability while facing implementation challenges related to data quality, model maintenance, and compliance requirements.
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Полякова, А. В. "ТЕХНОЛОГИЧЕСКИЕ ПОДХОДЫ К ВНЕДРЕНИЮ ГЕЙМИФИКАЦИИ В ОБРАЗОВАТЕЛЬНЫЙ ПРОЦЕСС". Человеческий капитал, № 5(197) (18 травня 2025): 136–44. https://doi.org/10.25629/hc.2025.05.13.
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В статье рассматриваются современные технологические решения, направленные на внедрение геймификации в образовательную практику. Проведён анализ цифровых инструментов с различной степенью кастомизации, включая специализированные SaaS-платформы, системы управления обучением (LMS), no-code/low-code конструкторы, а также решения на основе API и собственных разработок. Раскрыт потенциал каждой категории решений, а также определены их функциональные и методические ограничения. Полученные результаты могут быть использованы при проектировании образовательных сред, интеграции цифровых инструментов в учебный процесс и развитии систем управления обучением в контексте цифровой трансформации образования. The article discusses modern technological solutions aimed at introducing gamification into educational practice. The analysis of digital tools with varying degrees of customization is carried out, including specialized SaaS platforms, learning management systems (LMS), no-code/low-code constructors, as well as API-based solutions and proprietary developments. The potential of each category of solutions is revealed, as well as their functional and methodological limitations are identified. The results obtained can be used in the design of educational environments, the integration of digital tools into the learning process, and the development of learning management systems in the context of the digital transformation of education.
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Guresci, Emin, Bedir Tekinerdogan, Önder Babur, and Qingzhi Liu. "Feasibility of Low-Code Development Platforms in Precision Agriculture: Opportunities, Challenges, and Future Directions." Land 13, no. 11 (2024): 1758. http://dx.doi.org/10.3390/land13111758.
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Low-Code Development Platforms (LCDPs) empower users to create and deploy custom software with little to no programming. These platforms streamline development, offering benefits like faster time-to-market, reduced technical barriers, and broader participation in software creation, even for those without traditional coding skills. This study explores the application of LCDPs in Precision Agriculture (PA) through a systematic literature review (SLR). By analyzing the general characteristics and challenges of LCDPs, alongside insights from existing PA research, we assess their feasibility and potential impact in agricultural contexts. Our findings suggest that LCDPs can enable farmers and agricultural professionals to create tailored applications for real-time monitoring, data analysis, and automation, enhancing farming efficiency. However, challenges such as scalability, extensibility, data security, and integration with complex IoT systems must be addressed to fully realize the benefits of LCDPs in PA. This study contributes to the growing knowledge base in agricultural technology, offering valuable insights for researchers, practitioners, and policymakers looking to leverage LCDPs for sustainable and efficient farming practices.
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Siva Prakash Bikka. "Workflow Automation Engines: Driving Innovation in Cloud-Native and AI-Enhanced Business Processes." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 1 (2025): 282–89. https://doi.org/10.32628/cseit25111227.
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This comprehensive article examines the evolution and impact of workflow automation engines in modern business environments, focusing on their integration with cloud-native technologies and artificial intelligence. The article explores how these engines serve as fundamental enablers of digital transformation, offering organizations enhanced operational efficiency, process consistency, and scalability. The article shows various industry applications across healthcare, financial services, e-commerce, manufacturing, and public sectors, demonstrating the versatile benefits of workflow automation. It analyzes emerging trends, including AI integration, low-code/no-code platforms, hyperautomation, and cloud-native optimization, while addressing strategic implementation considerations such as cloud infrastructure integration, AI decision point orchestration, scalability planning, and cross-platform standardization. Through extensive analysis of real-world implementations and industry data, the article highlights how workflow automation engines have revolutionized business processes, enabling organizations to achieve operational excellence while maintaining flexibility and adaptability in an increasingly digital business landscape.
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Bala, Dhandayuthapani Veerasamy. "A pragmatic step to deploy low-code web apps on apex cloud services for emerging business assistance." i-manager’s Journal on Software Engineering 16, no. 3 (2022): 1. http://dx.doi.org/10.26634/jse.16.3.18697.
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Traditional approaches to web application development using the full-stack development model are inefficient. In today's rapidly changing business environment, organizations must rely on technology solutions that can be built and deployed in days or weeks, not months or years. Low-Code Development Platforms (LCDPs) compete with various features and technologies to provide business applications without prior knowledge of Internet technologies. Oracle Application Express (APEX) assists in the development of fantastic applications with little or no code in the Oracle database, as well as in the deployment of modern data-driven applications on the Oracle cloud platform, allowing users to quickly build secure business web applications with the best options., which can be accessed using an internet browser on desktop computers or mobile phones through its responsive web design without cost and time. Therefore, this paper demonstrates a pragmatic step toward deploying applications in a standalone database cloud using APEX services, which is focused on creating tables or converting spreadsheets into scalable, secure, and responsive web applications in minutes and providing automatic chart analysis reports for the business. As a result, individuals, Small- Scale Industries (SSIs), and Small and Medium Enterprises (SMEs) are encouraged to use cloud services that are always free with a 20 GB storage limit, which is outstanding resilience for cloudless web applications designed for new trends and business support free of charge. Machine learning in APEX Services can also be used to make web apps better for business intelligence in the future.
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Muhammad, Shakeel, Victor R. Prybutok, and Vikas Sinha. "Citizen Developers: The New Accelerators for Digital Transformation." Muma Business Review 8 (2024): 173–80. https://doi.org/10.28945/5426.
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In the context of this study, citizen developers are defined as individuals outside formal Information Technology (IT) departments who create applications using low-code/no-code platforms. The citizen developer role becomes pivotal as organizations navigate the intricate pathways to address increasing business demands for creating applications as part of their digital transformation journey. The driving force behind this paradigm shift lies in the ever-expanding appetite for software solutions that often eclipses the resource capacities of traditional IT departments. Consequently, companies are turning their attention toward citizen developers, entrusting them with crafting solutions. In this paper, we systematically review the existing literature to identify the factors contributing to citizen developers' effectiveness in creating applications. We discovered a lack of research papers discussing this topic. Our study fills this void and proposes a conceptual model to advance understanding of the factors that
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Pitkar, Harshad, Sanjay Bauskar, Devendra Singh Parmar, and Hemlatha Kaur Saran. "Exploring model-as-a-service for generative ai on cloud platforms." Review of Computer Engineering Research 11, no. 4 (2024): 140–54. https://doi.org/10.18488/76.v11i4.4017.
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This study examines the exploration of Model-as-a-Service for generative AI on cloud platforms. Model-as-a-Service (MaaS) could revolutionize generative AI; thus, we examine its impact on sectors, implementation best practices, and future trends. Business usage of generative AI for content development, predictive modelling, and consumer engagement is flexible and scalable using Software as a Service (SaaS). We explore how MaaS lets companies access, train, and deploy complex generative models like Generative Adversarial Networks (GAN), Variational Autoencoders (VAE), and Transformers without expensive in-house AI infrastructure. Lifecycle management in MaaS simplifies model training, deployment, versioning, and continuous improvement for iterative development in dynamic business contexts. MaaS security and compliance are crucial in highly regulated areas, including healthcare, finance, and law. Encryption, network isolation, and access control protect data and models. Generative AI models handle sensitive data; hence, industry standards and data sovereignty must be followed. Ethical AI, edge computing, and low-code/no-code platforms will enable more people to use models in real time and follow responsible AI guidelines, making MaaS's future bright. Generative AI applications and real-world case studies in healthcare, banking, retail, and entertainment demonstrate how MaaS can create value and stimulate innovation. Our study finds that using MaaS for generative AI, businesses can immensely benefit and explains how developers can speed up development, improve customer experiences, and remain ahead in the ever-changing digital landscape.
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Dileep Kumar Hamsaneni Gopalaswamy. "Industry-specific applications of oracle cloud technologies for integration and process automation." World Journal of Advanced Research and Reviews 26, no. 1 (2025): 3135–45. https://doi.org/10.30574/wjarr.2025.26.1.1357.
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Oracle Cloud Technologies offers a robust suite of services for integrating disparate systems and automating business processes across various industries. This report provides a comprehensive overview of the industry-specific applications of Oracle Cloud Integration and Process Automation, highlighting key use cases, benefits, recent trends, and challenges. The analysis indicates that these technologies are pivotal in driving digital transformation by enhancing efficiency, improving data management, and enabling innovation across finance, healthcare, manufacturing, retail, telecommunications, energy, and the public sector. The increasing adoption of Artificial Intelligence (AI) and Machine Learning (ML), the rise of low-code/no-code platforms, and the evolution of Robotic Process Automation (RPA) are shaping the future of these technologies, offering organizations unprecedented opportunities to optimize their operations. While significant advantages are evident, this report also addresses the security considerations and potential challenges associated with implementing Oracle Cloud Integration and Process Automation, emphasizing the importance of strategic planning and skilled resources.
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Ravi Mani. "Advances in Data Migration Tools for Cloud Billing Systems." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 1 (2025): 1130–39. https://doi.org/10.32628/cseit251112117.
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This article examines advancements in data migration tools for cloud billing systems. It highlights their impact on industries like healthcare, insurance, and telecommunications. It examines the key challenges faced during the migration of legacy billing systems to cloud platforms, including ensuring data accuracy, maintaining regulatory compliance, and minimizing operational downtime. The article delves into innovative solutions such as AI-powered ETL pipelines, automated data validation techniques, and metadata-driven frameworks, highlighting their features and benefits. Through case studies in healthcare and telecommunications, the article demonstrates the practical applications and outcomes of these advanced tools. Emerging trends like hybrid cloud migration, real-time data synchronization, blockchain for data integrity, and no-code/low-code platforms are discussed, offering insights into the future direction of billing system migrations. The article also addresses persistent challenges in data complexity, system downtime, and regulatory compliance, proposing strategic solutions. Finally, it explores future directions, including predictive analytics for risk identification, deeper integration of blockchain technology, and the potential of serverless architectures in data migration. This comprehensive article overview provides valuable insights for organizations planning or undertaking cloud billing system migrations, emphasizing the importance of adopting cutting-edge tools and strategies to ensure successful transitions in an increasingly digital landscape.
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Mohammed, A. Bukhari. "Citizen Development." International Journal of Computer Science and Information Technology Research 10, no. 2 (2022): 55–58. https://doi.org/10.5281/zenodo.6538521.
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<strong>Abstract:</strong> Citizen development is a process in business where software development, through the use of low-code/no-code (LCNC) platforms, is encouraged for employees without IT enterprise training. As a result, business users are facilitated with the necessary technology and IT support for the creation of basic productivity software. This paper expounds on citizen development by analyzing its history, benefits, promotion, framework, maturity assessment, governance, popular platforms, KPIs, and challenges, as well as its RACI. As a result, the IT department and its collaboration with citizen developers is essential toward the success of the citizen development process. Also, citizen development relieves the pressure felt by IT experts, thus improving creativity and enhancing technological skills in the process. A company that is able to build its own applications increases job efficiency, reduces IT backlog, and reduces operation costs. <strong>Keywords:</strong> Citizen, development, IT, KPIs, RACI, experts, developers. <strong>Title:</strong> Citizen Development <strong>Author:</strong> Mohammed A Bukhari <strong>International Journal of Computer Science and Information Technology Research</strong> <strong>ISSN 2348-1196 (print), ISSN 2348-120X (online)</strong> <strong>Vol. 10, Issue 2, April 2022 - June 2022</strong> <strong>Page No: 55-58</strong> <strong>Research Publish Journals (Publisher)</strong> <strong>Website: www.researchpublish.com</strong> <strong>Published Date: 11-May-2022</strong> <strong>DOI: https://doi.org/10.5281/zenodo.6538521</strong> <strong>Paper Download Link (Source):</strong> <strong>https://www.researchpublish.com/papers/citizen-development</strong>
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Shafi, Muzamil, and Manvendra Singh. "e-UNNAT and Public Service Guarantee Act 2011: Driving Reform in Jammu and Kashmir." Journal of Neonatal Surgery 14, no. 8S (2025): 756–61. https://doi.org/10.52783/jns.v14.2601.
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This paper explores the shift towards e-governance in Jammu and Kashmir (J&K) under the Digital India program, focusing on platforms like Jansugam.jk.gov.in and state.ras.gov.in. These initiatives aim to enhance administrative efficiency and citizen engagement by utilizing Low Code–No Code (LCNC) architecture, facilitating user-friendly service delivery. The Rapid Assessment System (RAS) further improves service quality by incorporating feedback and role-based access control. The e-UNNAT portal, consolidating over 1050 services, exemplifies the region's move to streamline service delivery, while the Public Services Guarantee Act’s auto-appeal system ensures timely service and accountability. Despite these advancements, challenges remain, including linguistic diversity, trust in technology, geographical barriers, and digital inequality, particularly in rural areas. This paper proposes a unique model to address these challenges, focusing on localized digital literacy campaigns, multilingual support, and community-based tech support networks. The model also emphasizes infrastructure development in underserved regions to bridge the digital divide. Overcoming these barriers is essential to ensure inclusive, effective e-governance and equitable access to public services in Jammu and Kashmir, ultimately improving governance and citizen satisfaction.
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Bhumeka, Narra Dheeraj Varun Kumar Reddy Buddula Hari Hara Sudheer Patchipulusu Navya Vattikonda Anuj Kumar Gupta and Achuthananda Reddy Polu. "The Integration of Artificial Intelligence in Software Development: Trends, Tools, and Future Prospects." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH IN MULTIDISCIPLINARY EDUCATION 3, no. 12 (2024): 1963–72. https://doi.org/10.5281/zenodo.15349360.
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Automation, optimization, and enhanced decision-making are just a few ways artificial intelligence (AI) changes thegame across several sectors. Its applications extend across diverse fields, including healthcare, transportation, finance, education,and software engineering. This study explores the integration of AI in software engineering, highlighting its transformative role instreamlining development workflows, improving software quality, and fostering collaboration between technical and non-technicalstakeholders. The rise of no-code and low-code platforms has democratized access to AI, allowing users with limited technicalexpertise to implement AI-powered solutions like NLP and predictive analytics. Key benefits of AI in software development includeautomation of repetitive tasks, early bug detection, efficient project management, and personalized user experiences. The study alsodiscusses the current trends in AI integration, including ML, NLP, robotics, and explainable AI, while addressing the challenges.Furthermore, AI tools for software development demonstrate their impact on education and skill development. Finally, the paperexplores prospects in AI-driven software development. By analyzing the current and future trends, this study provides insights intohow AI can shape the next generation of software development.
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Mahin, Md Rayhan Hassan, Estak Ahmed, Sharmin Sultana Akhi, et al. "Advancements and Challenges in Software Engineering and Project Management: A 2021 Perspective." Pathfinder of Research 2, no. 1 (2021): 17–31. https://doi.org/10.69937/pf.por.2.1.38.
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In the twenty-first century, major advancements emerged in software engineering and project management, propelled by the integration of artificial intelligence, cloud computing, automation, and innovative development approaches. Agile and DevOps consistently augmented software delivery efficiency, while AI-driven solutions advanced predictive analytics and automation. The emergence of low-code and no-code platforms enhanced software accessibility for non-technical users, while blockchain integration bolstered security and transparency. Nonetheless, obstacles including scalability concerns, cybersecurity risks, and regulatory compliance persisted as substantial impediments. Remote and hybrid work patterns need innovative project management tactics, including AI-based tracking tools and improved communication frameworks. Ethical issues related to AI bias and data privacy underscore the necessity for enhanced control in software development. This paper presents a thorough examination of these accomplishments and obstacles, providing insights into comparative trends from prior years and delineating future research areas. We advise researchers and practitioners to prioritize ethical AI, enhance project management frameworks, and fortify cybersecurity techniques. By tackling these issues, the discipline can progress toward more efficient, safe, and scalable software solutions.
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Muhammad, Shakeel, Victor Prybutok, and Vikas Sinha. "Unlocking Citizen Developer Potential: A Systematic Review and Model for Digital Transformation." Encyclopedia 5, no. 1 (2025): 36. https://doi.org/10.3390/encyclopedia5010036.
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Citizen developers, individuals outside formal IT departments who create applications using low-code/no-code platforms, are becoming increasingly pivotal as organizations navigate digital transformation. The driving force behind this paradigm shift stems from an exponentially growing demand for software solutions that consistently outpaces traditional IT departments’ capacity. Consequently, companies are turning their attention toward citizen developers, entrusting them with crafting solutions. In this work, we perform a systematic review of the existing literature to unearth the pivotal themes and subthemes and identify the factors contributing to citizen developers’ effectiveness. Our systematic review revealed a significant gap in scholarly understanding of factors contributing to citizen developers’ effectiveness. While some studies touched on these factors, none explored them comprehensively or provided an integrated framework for understanding their interrelationships. To fill this void, we propose a conceptual model to advance the understanding of the factors that influence the effectiveness of citizen developers in creating applications. While the model contributes to the theoretical understanding of citizen development, practical implications further reinforce its value. By leveraging the model, organizations can make informed decisions to enhance the productivity of citizen developers, align digital transformation strategies, and foster innovation.
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Mohini, Chaudhari, and Manisha Bharambe Dr. "The Future of Financial Security in Embedded Banking." International Journal of Advance and Applied Research S6, no. 22 (2025): 406–13. https://doi.org/10.5281/zenodo.15502000.
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<em>Today the transaction security in banking is the major concern because the data stored is not safe, higher changes of fraud, low security for bank transactions. This paper explores eight key innovations in embedded banking that are shaping the future of finance. The survey in bank shows that current technology used for storing the data and fraud detection, but higher-level security is required. AI-powered personalized banking enhances user experience by providing smart budgeting, automated savings, and fraud prevention. Biometric and behavioral authentication improve security, while no-code and low-code platforms allow businesses to integrate financial services effortlessly. Cross-border embedded banking simplifies global transactions with AI-driven currency conversion and blockchain-powered settlements. The rise of crypto currencies enables embedded crypto wallets, real-time fiat conversion, and decentralized finance (DeFi) lending. With the growth of the metaverse and Web3, financial services can be extended to virtual worlds. IoT-driven embedded finance automates payments through smart cars and home devices, while pay-as-you-go banking models provide flexible financial solutions. Lastly, green and sustainable banking promotes eco-friendly transactions by tracking carbon footprints and offering rewards for sustainable spending.</em> <em> These innovations are reshaping the financial ecosystem by making banking more accessible, secure, and efficient. As embedded banking continues to evolve, businesses and consumers can expect a more seamless, personalized, and integrated financial experience by providing the security. </em>
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Adya, Mishra. "Legacy System Modernization: Effective Strategies and Best Practices." International Journal of Leading Research Publication 1, no. 3 (2020): 1–7. https://doi.org/10.5281/zenodo.14769544.
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Legacy system modernization has become a pivotal concern for organizations striving to maintain competitiveness, security, and operational efficiency in today’s fast-moving technological landscape. This review paper explores the multifaceted nature of legacy systems—outdated platforms and applications that, despite reliability, pose escalating challenges in terms of maintenance cost, security vulnerabilities, and rigidity. It discusses the primary drivers for modernization, including stringent regulatory requirements, the need for agility in market responsiveness, and growing pressures to integrate emerging technologies like cloud computing and artificial intelligence. Building on these factors, the paper provides a detailed examination of various modernization approaches, from minimal interventions such as rehosting (“lift-and-shift”) to more ambitious strategies like refactoring, rearchitecting, and rewriting core applications. Best practices emphasize thorough assessment and roadmap development, incremental upgrades, cloud-native architectures, DevOps-driven continuous integration, and parallel migration to mitigate risks and minimize business disruption. Case studies illustrate how phased strategies and robust change management can yield substantial long-term benefits, including reduced technical debt, improved scalability, and greater adaptability to future innovations. Concluding with insights into upcoming trends—such as AI-enabled refactoring and low-code/no-code accelerators—the paper underscores how effective modernization not only safeguards mission-critical operations but also sets the stage for sustained organizational growth and digital transformation.