Checksum provides an AI-driven solution that automatically generates and maintains end-to-end tests using Playwright and Cypress, based on real user sessions. This technology eliminates the need for manual test creation and maintenance, ensuring comprehensive test coverage and real-time updates to prevent bugs from reaching production.
Funding
Funding not disclosed
Founders
Product
Problem
Creating and maintaining end-to-end (E2E) tests for web applications is a time-consuming and resource-intensive process, often requiring manual effort to write and update tests as the application evolves. Traditional testing methods struggle to keep pace with rapid development cycles, leading to incomplete test coverage and increased risk of bugs reaching production.
Solution
Checksum provides an AI-powered platform that automates the generation and maintenance of E2E tests, leveraging real user sessions to ensure comprehensive test coverage. The platform uses machine learning models trained on user behavior to automatically detect test flows, including both happy paths and edge cases. When application features are updated or new features are introduced, Checksum's AI agent automatically adjusts existing tests and generates new ones, eliminating the need for manual intervention. The generated tests are designed to be non-flaky, ensuring reliable and consistent results.
Target Audience
Checksum is designed for software development teams, QA engineers, and DevOps professionals who want to automate their E2E testing process, reduce manual effort, and improve the quality and reliability of their web applications.
Features
- Automated E2E test generation based on real user sessions and natural language test flows
- AI-powered test maintenance with self-healing capabilities to adapt to application changes
- Comprehensive test coverage, including happy paths and edge cases, identified through machine learning
- Support for generating tests in Playwright and Cypress frameworks
- Integration with GitHub and GitLab for seamless test delivery via pull requests
- Compatibility with CI/CD pipelines, including Jenkins and CircleCI
- Anonymized data collection to protect user privacy with minimal performance impact