SentinelQA

SentinelQA is an automated QA testing platform designed for web application testing. It executes automated browser tests, collects debugging artifacts, analyzes test stability, and provides a dashboard for test analytics.

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Features

SentinelQA provides multiple QA testing capabilities:

• Cross-browser testing (Chromium, Firefox, WebKit)
• Parallel test execution
• End-to-end automated testing
• Chaos testing (network and failure injection)
• Visual regression testing
• Flaky test detection
• Artifact collection (screenshots, videos, traces)
• Analytics dashboard for test insights

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Architecture

SentinelQA consists of four main components:

SentinelQA
│
├── core/
│   ├── test_runner
│   └── artifact_manager
│
├── analytics/
│   ├── metrics_collection
│   ├── visual_regression
│   └── flaky_test_detection
│
├── chaos/
│   ├── network_chaos
│   └── failure_injection
│
└── dashboard/
    └── test_analytics_dashboard

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Installation

1. Clone the Repository

git clone https://github.com/YOURNAME/SentinelQA
cd SentinelQA

2. Install Dependencies

pip install -r requirements.txt
playwright install

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Running Tests

Run SentinelQA

python sentinel.py

Run with Parallel Workers

python sentinel.py --workers 3

Run with Network Chaos

python sentinel.py --network slow

Run with Failure Injection

python sentinel.py --failure js_error

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Dashboard

Start the analytics dashboard:

python dashboard/app.py

Open in browser:

http://127.0.0.1:5000

The dashboard provides:

• Test metrics
• Failure screenshots
• Browser distribution
• Pass/fail analytics

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Artifacts

SentinelQA automatically stores test artifacts:

artifacts/
├── chromium/
├── firefox/
└── webkit/

Artifacts include:

• Screenshots
• Playwright traces
• Video recordings

These artifacts help debug failed tests.

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Example Use Case

SentinelQA can be used to:

• Test web applications across multiple browsers
• Simulate unstable network conditions
• Detect UI regressions
• Identify flaky tests
• Analyze failures through captured artifacts

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Roadmap

Future improvements planned:

• AI-assisted failure analysis
• Artifact explorer dashboard
• Prometheus / Grafana metrics support
• CI/CD integration

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Tech Stack

• Python
• Playwright
• PyTest
• Flask
• Chart.js
• Docker

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