iTaskDev: A software as a service with adaptive algorithm for optimized software development planning across methodologies (Record no. 37086)

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control field FT8788
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control field 20251112140221.0
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Classification number T5 M46 2025
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Personal name Mendoza, Aldren John M.; Nacilla, Norman Alexiz D.; San Gabriel, Charles Sherwin B.
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Title iTaskDev: A software as a service with adaptive algorithm for optimized software development planning across methodologies
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Date of production, publication, distribution, manufacture, or copyright notice c2025
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Other physical details Capstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2025
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Formatted contents note 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’s 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.
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Classification Filipiniana
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          Filipiniana-Thesis PLM PLM Filipiniana Section 2025-10-15 donation   T5 M46 2025 FT8788 2025-11-12 2025-11-12 Thesis/Dissertation

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