Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREMWP100
Volume:
9 |
5 |
May 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
In the rapidly changing software development environment of today, developing backend APIs that are not tied to particular database technologies is essential for ensuring flexibility, scalability, and compatibility across different platforms. This initiative suggests an AI-based approach to automatically create database-agnostic APIs, simplifying backend development and minimizing manual coding tasks. Utilizing machine learning and natural language processing methods, the system understands comprehensive user needs or schema specifications and produces fully operational RESTful APIs that facilitate CRUD operations, input validation, and error management. The created APIs work with various database systems (e.g., MySQL, PostgreSQL, MongoDB) by employing abstraction layers and ORM frameworks. This method enables developers to concentrate on business logic while speeding up development cycles, improving maintainability, and guaranteeing adaptability in various database settings. This solution is perfect for quick prototyping, corporate applications, and integration situations where backend adaptability is crucial.
KEYWORDS
Publication Date
5/19/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
2
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...