Status: In Development (LLM Integration Phase)
This application is designed to empower senior citizens by simplifying health and nutrition tracking. Built with a focus on accessibility and data integrity, the project serves as a primary environment for implementing advanced Quality Assurance and Compliance methodologies.
- 📝 Regression Suite # Comprehensive baseline testing for AI integration
- 📊 Bug Report # Standardized format for defect logging
- 🔄 Boundary Data Tables # Data sets used for boundary value analysis
- 🤖 AI Voice Scenarios # Data sets used for AI Voice analysis
Regression Testing: Rigorous testing of core manual input features during the deployment of the AI/LLM voice-command module.
Data Integrity Validation: Ensuring that physiological data is accurately stored and retrieved across different device types.
User Acceptance Testing (UAT): Focusing on the specific UI/UX needs of users aged 65+, prioritizing high-contrast visuals and simplified navigation.
docs/- Regression Suite # Comprehensive baseline testing for AI integration
- Bug Report # Standardized format for defect logging
test-data/- Boundary Data Tables # Data sets used for boundary value analysis
- AI Voice Scenarios # Data sets used for AI Voice analysis
README.md# Project overview and QA methodology