iTaskDev: A software as a service with adaptive algorithm for optimized software development planning across methodologies - Mendoza, Aldren John M.; Nacilla, Norman Alexiz D.; San Gabriel, Charles Sherwin B. (. ., 2025)
ABSTRACT: In software development, choosing the right Software Development Life Cycle (SDLC) model is critical but challenging due to the diversity of models, each tailored to specific project requirements. Many existing tools fail to fully leverage SDLC frameworks or provide robust automation. This study introduces a web-based workspace system designed to enhance software engineering projects be streamlining processes and improving efficiency. The proposed system integrates a Natural Language Processing (NLP) model, developed using Azure ML and the Open AI API, to recommend the most suitable SDLC model for a given project. This ensures accurate and context-aware suggestions, optimizing the development process. Additionally, a dynamic programming algorithm automation task allocation, adapting to the recommended SDLC to improve resource management and project flow. The system$1 (Bs automation capabilities were rigorously tested across various project scenarios to validate its effectiveness. To further enhance functionality, GiftHub API services were incorporated to provide comprehensive project analytics, leveraging repository commits and issue tracking for real-time insights. This web-based workspace system offers a cohesive solution for software development, combining intelligent SDLC recommendations, automated task management, and robust analytics. By addressing the limitations of existing tools, it paves the way for more efficient and adaptable software engineering practices, ultimately enhancing project outcomes.s
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Keywords: academic writing