I Built a Fault Injection Framework for On-Device AI in Flutter - And You Can Help!

Muhammad Assad Ullah — Tue, 28 Jul 2026 13:51:18 +0000

I Built a Fault Injection Framework for On-Device AI in Flutter - And You Can Help! 🧪

The Problem Nobody Talks About

On-device AI is exploding. Llama 3, Phi-3, Gemma — they're all running directly on phones and edge devices.

But here's the thing: nobody is testing what happens when these models fail.

When your AI model runs on a user's phone, it WILL fail:

Memory pressure → OOM crashes
Malformed input → Silent failures
Quantization drift → Garbage outputs
Thermal throttling → Slow inference

These issues only surface in production. Users experience crashes. Developers scramble to fix them. There's no tooling to test AI reliability before deployment.

Introducing SATE AI

So I built a framework to fix this.

SATE AI (Systematic AI Testing & Evaluation) is a fault injection framework for testing on-device AI models in Flutter applications.

What It Does

import 'package:sate_ai/sate_ai.dart';

final report = await SateAI.stress(
  model: MockAdapter(),  // Replace with your real model
  injectors: [
    MemoryPressureInjector(limitMb: 150),
    MalformedInputInjector(),
  ],
);

if (report.passed) {
  print('✅ Model passed stress test');
} else {
  print('❌ Model failed: ${report.failures.length} failures');
  print(report.toMarkdown());
}

Features

✅ Fault injection engine - Simulate memory pressure, malformed inputs, and more
✅ 59 unit tests - Full coverage of core modules
✅ MockAdapter - Test without real AI models
✅ StressReport - JSON + Markdown serialization
✅ Web Dashboard - Visualize test reports with charts
✅ Extensible - Add your own injectors and adapters

Watch It Catch a Failure

The dashboard shows exactly which faults caused the model to fail.

Why I Built This

I've been working with on-device AI and noticed a critical gap:

Every Flutter app tests its UI. Nobody tests its AI.

SATE AI is my attempt to make AI reliability testing as standard as UI testing.

The Tech Stack

Flutter/Dart - 100% Dart, no production dependencies
Mock Adapter - Pure Dart simulation for testing
Chart.js - Web dashboard for report visualization
GitHub Actions - CI/CD with 59 passing tests

Current Status

Feature	Status
Core Framework	✅ Complete
MemoryPressureInjector	✅ Complete
MalformedInputInjector	✅ Complete
Web Dashboard	✅ Complete
ONNX Runtime Adapter	⏳ In Progress
Quantization Drift Injector	⏳ Planned
Thermal Throttle Injector	⏳ Planned

📦 Published on pub.dev

SATE AI is officially published!

dependencies:
  sate_ai: ^0.1.0

🚀 How You Can Help

I'm building this solo, and I need YOUR help!

✅ Star the Repository

⭐ Star SATE AI on GitHub - It takes 2 seconds and helps others discover the project.

🔧 Pick a Good First Issue

We have 7 Good First Issues ready for contributors:

Add ONNX Runtime Adapter - Medium
Implement Quantization Drift Injector - Easy
Add TensorFlow Lite Adapter - Medium
Thermal Throttle Injector - Easy
Add Confidence Score Validation - Easy
Improve README Examples - Easy
Create Web Dashboard - Completed! ✅

📝 Share Your Feedback

Try SATE AI and open an issue
Suggest new fault injectors
Help improve documentation
Share the project with others

💬 Join the Discussion

We have active Discussions where we talk about:

Feature ideas
Technical questions
Show & Tell projects built with SATE AI

Join the conversation

Why Contribute?

For Your Career

Build your GitHub profile with real contributions
Work with Flutter + AI (fast-growing field)
Learn about fault injection and reliability testing
Get your PR merged into a pub.dev package

For the Community

Help make on-device AI more reliable
Shape the direction of the project
Be part of something from the ground up

Quick Start

# 1. Add the dependency
flutter pub add sate_ai

# 2. Write your first test
import 'package:sate_ai/sate_ai.dart';

final report = await SateAI.stress(
  model: MockAdapter(),
  injectors: [
    MemoryPressureInjector(limitMb: 100),
    MalformedInputInjector(),
  ],
);

print(report.passed ? '✅ Passed' : '❌ Failed');

📚 Resources

The Future of SATE AI

Here's what's coming:

Feature	Planned	Status
ONNX Runtime Adapter	v0.2.0	In Progress
Quantization Drift	v0.2.0	Planned
Thermal Throttle	v0.2.0	Planned
GitHub Action	v0.3.0	Planned
Research Paper	2026	Planned
More Injectors	Ongoing	Planned

💡 My Journey

I built this project in ONE DAY:

59 tests passing
2 working injectors
Professional documentation
Published to pub.dev
First contributor already!

Open source is about community. I can't build this alone.

⭐ Star the repo. Share this post. Pick an issue.

Every contribution counts - from reporting bugs to writing code to sharing the project with others.

👉 GitHub Repository 👈

Built on research from SATE/AndroTest24. Let's make on-device AI reliable! 🚀




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## 📋 Post Settings

| Setting | Value |
|---------|-------|
| **Title** | I Built a Fault Injection Framework for On-Device AI in Flutter - And You Can Help! |
| **Tags** | flutter, ai, testing, opensource |
| **Cover Image** | Upload a screenshot or GIF from the dashboard |
| **Series** | (Optional) "Building SATE AI" |

---

## 🎯 Publishing Checklist

- [ ] Copy the title
- [ ] Add tags: `flutter`, `ai`, `testing`, `opensource`
- [ ] Upload cover image
- [ ] Paste the entire body
- [ ] Click **"Publish"**
- [ ] Share the link on Twitter, LinkedIn, and Reddit

---

## 🔥 Bonus: Engagement Tactics

### After Publishing:

1. **Reply to every comment** within 24 hours
2. **Ping me on Twitter** - I'll retweet
3. **Share in Flutter Discord** - #showcase channel
4. **Post to r/FlutterDev** - Link to the DEV.to article
5. **Update your LinkedIn** - "I wrote about building SATE AI"

---

## 📊 Expected Impact

| Metric | Target | Timeline |
|--------|--------|----------|
| DEV.to Views | 1000+ | Week 1 |
| GitHub Stars | +20 | Week 1 |
| New Issues | +2 | Week 1 |
| Contributors | +1 | Week 2 |

---

## 🚀 Ready to Publish!

**Copy everything above and paste it into DEV.to!**

Let me know when you've published it and I'll help you with the next steps! 🎉

DEV Community: Muhammad Assad Ullah