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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.

This paper illustrates the power of extending Language Driven Engineering (LDE) with Domain-Specific Natural Languages (DSNLs) through a case study on two levels. Both cases benefit from the characteristic decomposition feature of LDE, resulting in tasks tailored to the application of domain-specific languages, here with a focus on the application of DSNLs supported by LLM-based code generation. In the first case study, we show how DSNL-supported LDE facilitates the development of point-and-click adventures, whereas the second case study focuses on migration: We demonstrate how the entire LDE scenario for point-and-click adventure games can be migrated to output TypeScript instead of JavaScript using LLM-based code generation exclusively, without manually writing any code. This migration not only infers the required types, but also preserves an important property of the original LDE scenario: generated web applications can be automatically validated by design via automata learning and subsequent model checking. Even better, this property can be exploited to automatically validate the correctness of the migration by learning so-called difference automata that characterize the behavioral differences between the generated JavaScript-based and Type-Script-based applications.

The rise of citizen developers utilizing Low Code/No Code (LC/NC) platforms marks a transformative shift in the software development landscape. As organizations face a shortage of skilled software developers, this study addresses the urgent need to leverage citizen developers – individuals without traditional technical backgrounds who can effectively contribute to software solutions using LC/NC platforms. Through a multi-layered research methodology that includes a literature review, analysis of job postings, and qualitative interviews, this paper provides a detailed characterization of the citizen developer role and delineates the specific skills and competencies necessary for success. The findings reveal that citizen developers typically occupy supplementary roles within organizations, highlighting the need for versatile, cross-functional skill sets that meet the evolving demands of modern businesses.To address this landscape, the study proposes a comprehensive framework designed to facilitate the integration of citizen developers into organizational IT strategies. This framework underscores the importance of aligning of re- and upskilling initiatives with organizational goals while fostering a culture of continuous learning. By doing so, this paper contributes to the discourse on evolving IT roles and socio-technical systems development. It offers a strategic roadmap for harnessing the potential of citizen developers to mitigate the developer shortage and enhance organizational agility in software development.

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.

This article presents a part of the industrial metaverse for electric drive system diagnostics. The advantages of using a low-code/no-code platform for electric drive systems diagnostics are demonstrated. Five diagnostic scenarios were developed, programmed, and implemented. The article demonstrates the implementation and use of the platform’s main functional blocks: a visualization block (which displays the state of electric machines in any user-friendly form—graphs, Park’s vector diagrams, or diagnostic curves); a digital twin block (which simulates various engine states); a digital twin block with an engine defect (which simulates faulty engine states); and an artificial intelligence block (which trains classification model to predict various engine states). Experiments on training the artificial intelligence block using a misalignment defect dataset are presented. The dataset was divided into six classes: engine operation with/without a defect under no load, engine operation with/without a defect under a 50% load, and engine operation with/without a defect under a 100% load. The workflow for training and using the model, the basic training approaches, and the distinguishability of the presented classes are demonstrated. The model training results are shown. The article presents a methodology for extensive testing of program functionality. The obtained results demonstrate the feasibility of implementing a low-code/no-code platform and the feasibility of solving the assigned tasks with its help, as well as the simplification and reduction in engineering solution development time.

This paper presents the design, implementation, and evaluation of a low-code document management and approval system developed on the Microsoft Power Platform. The solution integrates Power Apps, Power Automate, SharePoint Online, and Azure Active Directory to enable secure, traceable, and device-independent workflows for managing organizational documents. By combining graphical interfaces, automated approval logic, and enterprise-grade identity management, the system supports real-time collaboration and compliance with records’ governance standards. A comparative analysis with traditional enterprise content management and open-source web architectures demonstrates substantial advantages in deployment speed, scalability, and auditability. Empirical results from a six-week pilot involving multiple users indicate a reduction in approval cycle time, high user satisfaction, and strong cost-efficiency relative to conventional development models. The findings highlight how low-code ecosystems operationalize digital transformation by empowering non-technical users to automate complex workflows while maintaining security and governance integrity. This work contributes to the understanding of information system democratization, showing that low-code platforms can extend digital participation, improve organizational agility, and support sustainable operational efficiency across distributed environments.

Purpose The author reports on the chief obstacle to successful digital adoption, the resistance to change the fundamental way a firm is managed—one requiring a transformation from industrial-era management to digital-age thinking and management. Design/methodology/approach The author explains that it has become increasingly apparent that the most successful firms at digital transformation are being run very differently from industrial-era management practices. Findings As every company becomes a digital company, they need a distributed computing fabric to build, manage, secure and deploy applications anywhere. Practical implications The use of “low code/no-code technology” is now “rapidly becoming a priority for every organization’s digital capability building”. Originality/value The crucial learning: At Novartis, digital technology did not initially infuse itself throughout the firm as management initially hoped. Some Novartis managers began to realize that technologists and data scientists alone couldn’t bring about the kind of wholesale innovation the business needed, so they began pairing data scientists with business employees who had insight into where improvements in efficiency and performance were needed.

PurposeThe purpose of this study is to understand the concept of “Low Code No Code” applications and study its scope of application for web designing, rapid application development (RAD) and supply chain digitization (SCD).Design/methodology/approachA qualitative exploratory study was conducted for this exploratory study. A semi-structured open-ended questionnaire was prepared by the authors. Based on the questionnaire in-depth interviews were conducted with subject matter experts having more than 10 years of experience in the domain of supply chain management and digitization. The study questionnaire focused on the current reach and future potential of “Low Code No Code” platforms. A total of 20 responses were collected from experts as post this point thematic saturation was reached. A non-probabilistic convenience sampling was applied to identify the experts The data was content analyzed for themes.FindingsThe major findings that emerged from the study was that “Low Code No Code” platforms applications could be used across end-to-end SCD. The study also revealed that RAD through “Low Code No Code” platforms could reduce organizations dependency on coders. In the case of procurement, “Low Code No Code” applications could improve vendor and supplier management by streamlining processes. The cost-effective and easy-to-maintain “Low Code No Code” application development could help Medium and Small-Scale Enterprises level the playing field against large organizations. The lack of adoption strategy and low perceived usefulness was identified as major barriers to the adoption of “Low Code No Code” applications by organizations.Research limitations/implications“Low Code No Code” application-based automation would enable better utilization of organizational supply chain (SC) resources and capabilities. This would improve the sustainability performance of the firm. Furthermore, it would also enable the provision of SC services at a lower cost level, thus benefiting customers.Practical implications“Low Code No Code” application-based automation would help organizations to reduce the dependency on coders and Information Technology developers SCD. This could also allow SC managers to make more apps to be built in less time without the need of complex coding. This could potentially reduce app development costs toward digitizing SCs.Originality/valueTo the best of the authors’ knowledge, this was one of the very first studies regarding how “Low Code No Code” applications could revolutionize the SC using these app development capabilities. This study also provided an extensive study of Diffusion of Innovations and Technological Organizational Theory frameworks for in the context of “Low Code No Code” technology adoption.

No-code (NC) platforms empower individuals without IT experience to create tailored applications and websites. While these platforms are accessible to a broader audience, their usability for people with disabilities remains underexplored. This study investigated whether, with targeted training, people with disabilities could effectively use NC platforms to develop customized tools for their workplace, and whether these tools would be adopted by their peers. Conducted in collaboration with a sheltered workshop in Germany, the study had three phases. Phase I involved a brainstorming session with employees, which shaped the study design and product development. In Phase II, six participants with disabilities received a one-week training to develop chatbots. Phase III implemented the chatbots in the workshop. In Phase II, each participant successfully developed four chatbots, which increased the participants’ skills and motivation. Based on the phase III results, users rated the developed chatbots highly (the System Usability Scale (SUS) questionnaire was delivered in the form of a chatbot), indicating their user-friendliness (M = 88.9, SD = 11.2). This study suggests that with appropriate training, individuals with disabilities can use NC platforms to create impactful, customized tools that are user-friendly and accessible to their peers.

Software development cycles in the context of IoT! (IoT!) applications require the orchestration of different technological layers, and involve complex technical challenges. The engineering team needs to become experts in these technologies and time delays are inherent due to the cross-integration process because they face steep learning curves in several technologies, which leads to cost issues, and often to a resulting product that is prone to bugs. We propose a more straightforward approach to the construction of high-quality IoT applications by adopting model-driven technologies (DIME and Pyrus), that may be used jointly or in isolation. The presented use case connects various technologies: the application interacts through the EdgeX middleware platform with several sensors and data analytics pipelines. This web-based control application collects, processes and displays key information about the state of the edge data capture and computing that enables quick strategic decision-making. In the presented case study of a Stable Storage Facility (SSF), we use DIME to design the application for IoT connectivity and the edge aspects, MongoDB for storage and Pyrus to implement no-code data analytics in Python. We have integrated nine independent technologies in two distinct Low-code development environments with the production of seven processes and pipelines, and the definition of 25 SIBs in nine distinct DSLs. The presented case study is benchmarked with the platform to showcase the role of code generation and the reusability of components across applications. We demonstrate that the approach embraces a high level of reusability and facilitates domain engineers to create IoT applications in a low-code fashion.