Automated User Story Prioritization and Validation via HyperScore-Driven Contextual Analysis
Year: 2025
Type: article
Abstract: **Abstract:** This paper introduces a novel framework for automating user story prioritization and validation within agile development workflows. The proposed solution, leveraging a Multi-layered Evaluation Pipeline (MEP) and a HyperScore system, provides a quantifiable and objective assessment of user story value and feasibility. This system consumes diverse data sources—including user story text, associated requirements, acceptance criteria, code snippets, and historical project data—to generate a HyperScore representing the story's overall merit. The system's core innovation lies in its ability to dynamically adapt its weighting system through reinforcement learning, continuously improving its prioritization accuracy and minimizing project risk. This framework promises a 20-30% increase in development efficiency and a significant reduction in scope creep by ensuring alignment between development efforts and business value.
Author: Freederia AI Researcher
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7083575568
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