Checksum - AI-Powered End-to-End Testing Automation
Checksum empowers developers to quickly and autonomously generate comprehensive end-to-end tests by harnessing the power of artificial intelligence. With Checksum, users can save development time, ensure flawless test coverage, and seamlessly integrate AI-generated tests within their existing workflows.
Checksum Product Information
What is Checksum?
Checksum leverages AI to automatically generate and maintain end-to-end tests based on real user sessions, enabling developers to achieve comprehensive coverage with minimal effort. By training an AI model on actual user interactions, Checksum produces Playwright or Cypress tests that cover both happy paths and edge cases. The autonomously generated tests ensure maximum coverage, adapt to new features, and require minimal to zero maintenance, allowing teams to focus on innovation and rapid development.
How to Use Checksum?
To generate end-to-end tests, users can choose an auto-detected flow or define their own test flow using natural language. By integrating Checksum with just a few lines of JavaScript, developers can seamlessly incorporate AI-generated tests within their testing suite. With simple and convenient integration to popular tools like Playwright, Cypress, Github, Gitlab, Jenkins, and CircleCI, Checksum facilitates effortless adoption within existing workflows.
Core Features of Checksum
- Auto-generated end-to-end tests using Playwright or Cypress
- Comprehensive test coverage based on real user interactions
- Autonomous testing suite with self-maintaining and self-healing capabilities
- 5-minute integration with minimal impact on performance
Use Cases of Checksum
- Rapid end-to-end test generation and maintenance
- Effortless integration within existing development workflows
- Streamlined autonomous testing with minimal maintenance requirements
FAQ about Checksum
How are you generating the tests and what is your coverage?
We train an AI model on real user sessions from your production environment to learn typical and edge case flows. The model then generates tests covering both happy paths and edge cases.
How can you test new features if your model is trained on user sessions?
Our model can extrapolate from production sessions, learning UI conventions and generating tests for new features without requiring new sessions.
What kind of tests are you generating?
Checksum.ai employs machine learning to generate end-to-end tests using Cypress or Playwright code.
What data are you collecting? Do you impact my production performance?
To train the model, we record user sessions, but can work on staging only or anonymize data collection to protect user privacy. Our impact on performance is negligible, as we use proven open-source tools.
Is the SDK integration required?
Not necessarily. We can also use help articles to teach the model, and can discuss feasibility during a demo.
I have more questions
Simply use the Chat Bubble on the bottom right of the screen to ask us anything. We are here to help!
Checksum Badge
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