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.
Implementing unit test coverage enables the early detection and prevention of over 10 different kinds of bugs, such as logic errors, state management issues, and validation errors
Enhanced Code Quality
Maintaining unit test coverage promotes well-structured, readable, and maintainable code that follows best programming practices, such as SOLID principles.
Streamlined Development Process
Unit tests help identify potential issues quickly, thus reducing time spent on debugging. This allows your team to focus on delivering new features more efficiently.
Deploy Stress Free
Ensuring code changes pass all unit tests helps to maintain the stability of existing features and minimizes the risk of regressions. With comprehensive test coverage, developers can deploy new releases with increased confidence.
SuPported state management
Provider, Bloc, Riverpod or Getx. It works with all.
Welltested supports all kinds of architectures like MVVM, Clean architecture and state management solutions as long as the basic testability principles are followed.
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.
What parts of my code is collected? Is it used for improving the models?
We only analyze code and context required to generate unit test cases, i.e. the classes marked for testing and their dependencies. 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.
Why do we perform so well for Flutter/Dart?
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.