Prevents Bugs Early On.
Adding unit and widget tests as you write code helps early prevention of over 10 different kinds of bugs, such as logic errors, state management issues, and validation errors
Welltested Octoberfest is live! 🎉 Â
Launch blogFirst in world autopilot that generates exhaustive unit, widget and integration tests for your Flutter apps.
Our autopilot works alongside you and generates thoughtful test cases for your code.
Built by Flutter Engineers, welltested has custom-trained models for Flutter development workflows.
You can generate tests for Flutter and Dart code for Mobile, Web and Desktops. We support variety of architecture and state management choices like Provider, Bloc, Riverpod, Getx and more.
Developers aren't required to shift between IDEs to generate tests. Our AI comes as a pub.dev dependency that works directly with your Flutter codebase.
Just mark any class that you want to test with @Welltested annotation and the tests will be generated automatically.
Our AI-driven, meticulously crafted unit test cases simulate a wide range of input conditions, edge cases, and user interactions to ensure that the code behaves as expected under every possible condition.
You can also provide us your own ideal behaviour scenarios and we'll cover them as well.
Our AI system is designed to learn from its mistakes. If you come across any syntax issues or errors in the generated tests, simply make the necessary fixes and save the final test back to our system. Our AI will analyze these changes and learn from them, preventing the same mistakes from happening again.
Adding unit and widget tests as you write code helps early prevention of over 10 different kinds of bugs, such as logic errors, state management issues, and validation errors
Integration tests can be run across multiple devices at once with the help of Firebase Test Lab. This ensures your app works across all OS, screen sizes and hardware.
Maintaining test coverage promotes well-structured, readable, and maintainable code that follows best programming practices, such as SOLID principles.
Eliminate the risk of breaking existing features when you deploy and be assured that 100% of your app works before you release.
Welltested supports all kinds of architectures like MVVM, Clean architecture and state management solutions as long as the basic testability principles are followed.
Monthly
6 months
Ideal for personal projects and trying our testing AI.
Designed for production projects and growing startups.
Tailored for organizations with multi-project needs.
Ideal for personal projects and trying our testing AI.
Designed for production projects and growing startups.
Tailored for organizations with multi-project needs.
Monthly
Annually
Ideal for personal projects and trying our testing AI.
Designed for production projects and growing startups.
Tailored for organizations with multi-project needs.
Ideal for personal projects and trying our testing AI.
Designed for production projects and growing startups.
Tailored for organizations with multi-project needs.
Yes, you can get started with an individual plan to understand how Welltested works and later upgrade to a starter or enterprise plan for best quality generations and complete data protection.
We only analyze code and context required to generate unit test cases, i.e. the classes marked for testing and their dependencies.
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If you're a startup or enterprise customer, your data is fully private and we don't use it to improve our models.
For individual users, we use the generated test data to enhance our models and improve the unit tests quality for all users.
Our exceptional performance for Flutter/Dart unit testing stems from our team's deep expertise in Flutter engineering. We have invested significant time in:
1. Crafting tailored prompts specifically designed for Flutter/Dart unit tests,
2. Arranging these prompts in a sequence that produces well-structured and meaningful tests,
3. Analyzing not just the code being tested, but also its supporting context to generate tests with minimal syntax issues, and
4. Developing our own comprehensive dataset of unit tests, covering various libraries, state management solutions, and code architectures.
This meticulous process ensures our tests not only improve code understanding but also identify edge cases and enhance overall code robustness.