Software Requirements Specification (SRS) & Product Documentation
A complete requirements-engineering and product-design documentation set for a location-based system that matches patients with the nearest pharmacy holding a needed medicine in stock — including on-duty (nöbetçi) pharmacy filtering, a pharmacist stock panel, and an admin verification panel.
📄 This is a business analysis / product documentation portfolio project. It demonstrates the full analysis toolkit: user stories, story mapping, use case modeling, wireframing, storyboarding, and non-functional requirements definition.
When patients urgently need a specific medicine, they call or visit pharmacies one by one with no visibility into stock. PharmaFinder digitalizes stock information flow between pharmacies and gives patients a single answer: the nearest pharmacy that has your medicine, right now.
- Medicine search by name with live stock status
- Location-based pharmacy listing with directions (Google Maps / OpenStreetMap)
- On-duty (nöbetçi) pharmacy filtering
- Pharmacist panel: stock entry and working-hours management
- Admin panel: system oversight and pharmacy verification
- AI-powered OCR prescription recognition (≥90% accuracy target)
| # | Document | Contents |
|---|---|---|
| 1 | Introduction & Requirements | Purpose, product scope, target audience, references, requirements |
| 2 | Non-Functional Requirements | Performance (≤3s search, 100K queries/day), health & data compliance (KVKK/GDPR), security |
| 3 | User Stories | Role-based user stories: patient, pharmacist, administrator |
| 4 | Story Map | User-journey story map across the product backbone |
| 5 | Use Cases | 5 use case diagrams & fully specified use case forms (search & geo-listing, OCR prescription recognition, stock entry, alternative-medicine suggestion, pharmacy verification) |
| 6 | Wireframes | User / pharmacist / admin / results panel wireframes |
| 7 | Storyboard | End-to-end user scenario storyboard |
- Performance: search results in ≤3 seconds; designed for 100K queries/day
- Compliance: KVKK/GDPR-aligned personal & health data handling
- AI: OCR-based prescription recognition with a ≥90% accuracy target
- Integrations: Google Maps API / OpenStreetMap for geolocation and routing
Burak Sezer — Management Information Systems, Sakarya University Business analysis, requirements engineering, and product documentation.
Original documentation language: Turkish.