# Algorithms in Low-Code-No-Code for Research Applications: A Practical Review
## 6 Demonstration of LCNC Adoption in Modern Research
As shown in Table 3, the main reasons for solving research problems with LCNC were to obtain research data and generate AI-driven insights with complex algorithms (e.g., regression, clustering, deep learning, classification, sentiment analysis, entity recognition, etc.) without having to manually code them. Modern LCNC platforms have allowed non-programmer scientists and researchers to quickly obtain their research data from multiple sources and analyze their data with AI algorithms. During the course of this review study, it was also practically demonstrated how to obtain cyber-attack data (Figure 3), analyze the data with AI algorithms (Figure 4), perform CNN-based deep learning (Figure 5), visualize the information (Figure 6), and deploy the solution on mobile platforms (Figures 7 and 8) using LCNC platforms without manually writing codes in any programming languages. In summary, this study found the following core benefits of using LCNC platform to solve research problems:

* AI-powered tools: AI is increasingly being used to enhance low-code and no-code platforms, making it easier to build applications and automate tasks. Indeed, AI can be used to generate code, suggest best practices, and improve the overall efficiency of the development process. * Improved user experience: There has been a focus on improving the user experience of low-code and no-code platforms, making them more accessible and intuitive for users. This includes improvements in drag-and-drop interfaces, visual representations of data and workflow, and other features that simplify the development process. * Integration with other tools: Low-code and no-code platforms are now integrating with a variety of other tools and platforms, including cloud platforms, databases, and third-party APIs. This allows users to build more complex applications and connect them with existing systems. * Increased Adoption: Low-code and no-code technology is becoming more widely adopted, particularly among businesses. This is due in part to the ease of use and rapid development times that these platforms offer, as well as the ability to build applications that meet specific business needs. Overall, low-code and no-code technology is continuing to evolve and expand, offering more advanced features and capabilities to users. This technology is likely to become increasingly popular and widely adopted in the coming years. Modern LCNC platforms provide competitive advantages in solving critical research questions predominantly through their AI-based data analysis and information processing capabilities. Widespread adoption of LCNC platforms within the research community will be seen once critical concerns, such as ongoing cost commitments and vendor lock-ins are addressed. However, it is unlikely that LCNC platforms will completely remove the requirement of hand-coding in future, since it is not a revolutionary technology [77]. **Funding:** This research received no external funding. **Institutional Review Board Statement:** Not applicable. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** Data will be made available upon request. **Acknowledgments:** The author would like to thank Kaspersky for allowing autonomous download of cyber-attack statistics from their website (i.e., [[https://statistics.securelist.com/](https://statistics.securelist.com/)]([https://statistics.securelist.com/](https://statistics.securelist.com/)) (accessed on 3 January 2023)). Because of this anonymous access to Kaspersky site, it was possible to practically demonstrate the development of a cyber-intelligence solution with Microsoft Power Platform. **Conflicts of Interest:** The author declares no conflict of interest. ## References

* (1) Computer History Museum, Birth of Computer--ENIAC, CHM. [Online].