💍 Oura Ring Software Test Engineering Clone & Automation Suite

A purpose-built Software Test Engineering portfolio project demonstrating Full-Stack QA Automation, Chaos Engineering, and CI/CD pipelines for mobile health applications.

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🎯 Overview

This repository houses a simulated health-wearable application ecosystem. It was explicitly designed from the ground up to showcase modern Software Test Engineering (STE) principles. Rather than just building a functional app, the objective of this project is to build a highly testable system and thoroughly validate its integrity under stress.

The architecture mimics a simplified version of the Oura ecosystem:

1. Frontend: A React Native (Expo) mobile dashboard with premium dark-mode aesthetics displaying Sleep, Activity, and Readiness scores.
2. Backend: A Python FastAPI server providing dynamic mocked biometric data.
3. Testing Infrastructure: A robust suite including Pytest API validation, Appium UI automation, static type checking (Pyre), and an automated GitHub Actions pipeline.

🛠️ Core Technologies

• Mobile Frontend: React Native, Expo, TypeScript
• Backend Services: Python 3.11, FastAPI, Uvicorn
• Test Environment: Pytest, Pytest-HTML, Appium (UI Automation)
• Static Analysis: Pyre (Strict Type Checking)
• CI/CD: GitHub Actions

✨ Key STE Features

1. "Chaos Mode" Fault Injection API

To test the resilience of the mobile application and the rigor of the test suite, the FastAPI backend includes a bespoke Chaos Mode. When activated, it stochastically introduces:

• Malformed JSON payloads.
• HTTP 500 Internal Server Errors.
• Simulated high-latency packet drops. This forces the automation suite to validate error boundaries and frontend recovery mechanisms, not just the "happy path."

2. Design for Testability (DFT)

The React Native frontend is built with strict DFT principles:

• Every interactive component, screen, and text node is annotated with testID and accessibilityLabel.
• This ensures deterministic selector querying for Appium UI automation, drastically reducing E2E test flakiness.

3. Automated Validation Pipelines

The project features a comprehensive .github/workflows/test.yml GitHub Actions pipeline that:

• Configures a dual-runtime environment (Node.js & Python).
• Executes Pyre static analysis to catch type regressions.
• Runs the Pytest API automation suite against schema validations.
• Generates and stores comprehensive pytest-html reports as pipeline artifacts.

🚀 Getting Started

Prerequisites

• Node.js (v20+)
• Python (3.11+)
• Expo CLI (npm install -g expo-cli)

Installation & Execution

1. Start the Backend API

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt
python run_backend.py

(The backend runs on http://localhost:8000)

2. Start the Frontend Application

cd frontend
npm install
npx expo start

(Use the Expo Go app on iOS/Android or an emulator to launch the dashboard)

3. Run the Automation Suite

# Ensure the backend is running first
pytest tests/ -v --html=report.html --self-contained-html

🐛 Bug Tracking & Issue Management

Real-world STE involves rigorous bug documentation. See BUG_REPORTS.md for examples of deeply investigated issues (e.g., RNG seed flakiness, Pyre static analysis limitations, and Android ADB Reverse networking blockers), including root cause analysis and reproduction steps.

🔮 Future Roadmap

• Connect tests/test_ui_structure.py Appium scripts to a cloud device provider (e.g., AWS Device Farm) for multi-device regression.
• Implement strict Zod schema validation on the React Native payload consumption.
• Stabilize the Chaos Mode integration tests using deterministic RNG seed overriding.

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Created by a Software Test Engineering candidate aiming to ensure the highest quality standards for wearable health technology.