What is Checksum?
Checksum.ai is an end-to-end (E2E) automation testing tool that converts user sessions into a comprehensive testing automation pipeline for faster testing without compromising quality. The tool automatically generates and maintains E2E tests based on user sessions, reducing development time and allowing teams to focus more on shipping. It uses machine learning (ML) models specifically trained on the software's production sessions for full coverage. The tool does not require maintenance, as its AI adaptation updates tests to code changes and flakiness. Checksum.ai offers an integration process that is quick and easy. A seed test user on the production or staging environment is provided to generate tests, and the javascript software development kit (SDK) is integrated by pasting three code lines when the application is mounted. Integration is made simple with the tool's automatic and privacy-centric data collection. The data collected is similar to Fullstory or Hotjar, but inner texts are hashed for user privacy. Test results are generated using open-source frameworks such as Cypress or Playwright, and issues are detected immediately, reducing firefighting and speeding up code reviews. The tool offers an FAQ section that addresses common concerns, including how tests are generated, how new features are tested, what tests are generated and what data it collects. Checksum.ai's algorithms extrapolate from production sessions, learning user interface conventions, and generating tests for new features on the spot. The tool records user sessions in a similar way to Fullstory or Hotjar, hashes inner texts for privacy, and allows configurable privacy controls for sensitive elements. Despite its robust functionality, the tool has a non-existent impact on performance, using open-source tools used by Fortune 500 companies.
Pros
- User session-based testing
- End-to-end automation
- Auto generates/maintains tests
- Reduces development time
- Aids in faster shipping
- Trained on production sessions
- Full coverage testing
- No maintenance required
- Adapts tests to code changes
- Quick integration process
- Seamless SDK integration
- Automatic & privacy-centric data collection
- Hashed inner texts for privacy
- Open-source framework use
- Immediate bug detection
- Speeds up code reviews
- Test results via Cypress or Playwright
- Generates tests for new features
- Configurable privacy controls
- Non-existent performance impact
- Functionalities of FullStory and Hotjar
- FAQ section for common queries
- Detects code change flakiness
Cons
- Requires user session recording
- Reliance on open-source testing frameworks
- Requires SDK integration
- Privacy concerns (hashed inner texts)
- Requires production environment access
- Limited customization options
- May not handle complex interfaces
- New features testing uncertainty
- Could fail to update tests
Checksum FAQ
What is Checksum.ai and what does it specialize in?
Checksum.ai is an end-to-end (E2E) automation testing tool that specializes in converting user sessions into a complete testing automation pipeline. It facilitates higher quality testing outputs and allows for faster testing without sacrificing quality.
How does Checksum.ai use user sessions in its testing process?
Checksum.ai uses user sessions to generate and maintain E2E tests. The tool is designed to reduce development time and enables teams to focus more on product development by automatically constructing E2E tests based on the user sessions.
How does Checksum.ai ensure higher quality testing output?
Checksum.ai ensures higher quality testing output by automatically transforming user sessions into a comprehensive testing automation pipeline. This aids in testing the application extensively without skipping any feature, thus preventing the introduction of new bugs and reducing the firefighting, leading to a more quality output.
What is the role of machine learning models in Checksum.ai?
Machine learning models in Checksum.ai are specifically trained on the software's production sessions allowing for full testing coverage. These models learn user behaviour from user sessions, and are used to generate tests. The ML models then conduct edge case testing and produce automated tests, thus playing a significant role in the testing process.
What are the maintenance requirements for Checksum.ai?
Checksum.ai does not require maintenance. It is designed with a self-adapting AI that adjusts and updates the tests according to the modifications in the code and flakiness.
How does the integration process for Checksum.ai work?
The integration process for Checksum.ai is designed to be fast and straightforward. It consists of integrating a Javascript SDK by pasting three lines of code when the application is launched. A seed test user is provided on the production or staging environment to generate tests.
Can you project the kind of data Checksum.ai collects for its operations?
Checksum.ai collects data similar to tools like FullStory or Hotjar, recording user sessions for training the models. All the inner texts are hashed to ensure user privacy. The tool also requires a seed test user from the production or staging environment to generate tests.
What is the role of the JavaScript SDK in Checksum.ai and how is it integrated?
The JavaScript SDK in Checksum.ai is important for integrating the tool into the application. It is as simple as pasting three lines of code when the app is mounted. This SDK helps the tool record user sessions and generate tests based on this data.
