Treffer: An integrated tools for automatic software artifacts generation.

Title:
An integrated tools for automatic software artifacts generation.
Source:
AIP Conference Proceedings; 2026, Vol. 3326 Issue 1, p1-18, 18p
Database:
Complementary Index

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The creation of software artifacts, which are crucial components in software development encapsulating the architecture and functionalities of a software system, often relies on manual methods. This approach is time-consuming, error-prone, and inconsistent, which can hinder development progress and affect the overall quality of the final system. Recent advances suggest that automated software artifact generation tools can enhance efficiency and consistency in the development process. This study aims to develop and validate an integrated tool for automatically generating various software artifacts to improve software development efficiency, accuracy, and consistency. The methodology involved the development of a Software Artifact Generator using Django's multiple-application architecture. This approach facilitated the creation and integration of distinct applications, each responsible for specific aspects of the artifact generation process. The methodology was structured around key activities such as project setup, application creation, model configuration, view development, URL mapping, and template design. Both sequential and parallel output generation workflows were implemented and tested. The analysis identified significant variations in database structures, workflows, and input/output formats across 16 existing applications developed by different teams. Integration involved carefully handling these differences, standardizing data formats, and implementing a unified API gateway to ensure seamless data exchange. The integrated tool successfully demonstrated sequential and parallel output generation, ensuring scalability, maintainability, and efficiency. The developed tool effectively addresses the challenges of manual artifact creation by providing a robust framework for automated generation. This enhances productivity and software quality by minimizing errors and inconsistencies. Future research should focus on refining these techniques and exploring additional functionalities to support a broader range of software artifacts. [ABSTRACT FROM AUTHOR]

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