Systematic Literature Review of Low-Code and Its Future Trends
With the growing demand for software, it is necessary to look for new approaches that allow faster de-liveries, without compromising the quality of the final product. Among these new approaches to development is low-code, which emerged as a proposal for applications development, minimizing the need for manual coding. Its application is associated with the use of low-code development platforms (LCDPs), a term most commonly used when discussing low-code in general. This work presents the results obtained from a Systematic Literature Review (SLR), which sought to understand the current state and future trends of the low-code approach to be considered by software engineers as an alternative to high-level programming languages. Applying knowledge of Software Engineering would take care of the quality of the process and the product. This would allow the decrease of time and costs in the construction of software. Fol-lowing Kitchenham's methodology, the characteristics, benefits, challenges and trends of low-code were identified. Although low-code has gained significant ground, there is a notable gap in comprehensive SLRs focused exclusively on this approach, as it is often discussed in conjunction with the no-code approach. After examining various databases such as IEEE Xplore, ACM Digital Library, ScienceDirect, and SpringerLink, fifteen rele-vant primary studies (published between 2018 and 2023) were selected. Among the findings, it was discovered that the characteristics of LCDPs include to use graphical interfaces, support for external services, collaborative development and reuse. The benefits encompass rapid development, cost reduction, ease of use and strong integration. However, challenges such as lack of customization and scalability are faced. Future trends include adoption by small and medium sized enterprises (SMEs), integration with DevOps, and digitalization efforts. Careful evaluation is recommended for effective implementation of low-code approach.
Authors
- Lizbeth A. Hernández-González (ORCID: https://orcid.org/0000-0002-8524-3209)
- Christian Pérez-Salazar (ORCID: https://orcid.org/0000-0001-8542-4344)
- Ángel J. Sánchez-García (ORCID: https://orcid.org/0000-0002-2917-2960)
- Axel Panamá Velásquez
Institutions
- Universidad Veracruzana (MX)
Publication Details
- Published
- 2024-10-28
- DOI
- https://doi.org/10.1109/conisoft63288.2024.00015
- Citations
- 2
- Primary Topic
- Advanced Computing and Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 3.92