Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
VDA-SDLC: Validation-Driven Adaptive Agentic Software Development Life Cycle Framework for Autonomous Software Engineering. |
| Συγγραφείς: |
K., Deepthi1, Chalageri, Sunita1 |
| Πηγή: |
International Scientific Journal of Engineering & Management. May2026, Vol. 5 Issue 5, p1-6. 6p. |
| Θεματικοί όροι: |
*Intelligent agents, Software validation, Automation software, Language models, Multiagent systems, Code generators, Requirements engineering |
| Περίληψη: |
This paper presents a Validation-Driven Adaptive Agentic SDLC Framework that automates multiple software engineering activities through a collaborative multi-agent architecture. The proposed framework integrates specialized agents responsible for requirement analysis, planning, code generation, validation, and packaging. Unlike conventional AI coding assistants, the framework employs a validation-driven feedback mechanism in which generated applications are automatically verified before deployment preparation. When inconsistencies or incomplete outputs are detected, corrective feedback is provided to the generation stage to improve software quality. The framework utilizes OpenRouter-based Large Language Models including DeepSeek, Qwen, and GPT-OSS for frontend application generation. The architecture was implemented using FastAPI and evaluated through the generation of multiple frontend applications including calculators, weather dashboards, password generators, task management systems, and quiz applications. Experimental observations indicate that the proposed architecture successfully automates major frontend SDLC activities while improving application consistency and reducing manual development effort. The proposed framework demonstrates the feasibility of autonomous software engineering using validation-driven agent collaboration and provides a foundation for future full-stack autonomous development environments. [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: |
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