End-to-end (E2E) testing is a type of software testing that validates the complete and integrated functionality of an application. The purpose is to make sure that the product works as expected, from start to finish, including all its components and dependencies.
In E2E testing, you simulate real-world scenarios to test how the product behaves from the user’s perspective. This means testing the full flow of the application, from the user interface down to the database, and any integrations with external systems or services. The goal is to catch issues that might be missed in more isolated tests like unit or integration tests.
For example, in a web application, E2E testing would involve steps like:
Opening the web browser.
Navigating to the login page.
Entering user credentials.
Submitting the login form.
Verifying that the user is redirected to the correct page.
E2E tests can be automated or done manually.
In summary, E2E testing ensures that the entire application, from user interaction to the backend, works together as intended.
End-to-end testing is beneficial for a wide range of businesses, especially those that rely heavily on software for their operations or customer interactions.
In summary, any business that depends on complex, integrated software systems to deliver products, services, or customer experiences can benefit from E2E testing. It helps ensure that the entire system functions as intended, reducing the risk of failures that could impact the business.
Replicates the user experience:
End-to-end (E2E) testing closely mirrors how real users interact with your application. It allows you to test the entire flow from start to finish, ensuring that all parts of the system work together seamlessly. By simulating real-world scenarios, E2E tests can catch issues that might be missed by more isolated tests, like unit or integration tests.
QA.tech have ingested countless sessions of user behaviour to tune our AI agent testing to behave just as regular users.
Comprehensive system testing:
E2E tests cover the entire stack, from the user interface to the backend services and databases. This holistic approach helps ensure that all components, such as the frontend, backend, APIs, and even third-party integrations, work in harmony. It’s particularly useful for catching issues that arise due to the interaction between different parts of the system.
Complexity and multiple dependencies:
E2E tests involve many moving parts, which makes them inherently complex. Since these tests cover the full application stack, they depend on several components being correctly configured and available. Managing these dependencies can be challenging, especially as your application grows in complexity. By using AI agent testing your tests will be much more robust and reliable to changes due to the smartness involved.
Potential for flakiness:
E2E tests are notorious for being flaky, meaning they can sometimes fail without a clear reason. Even when there’s no actual problem with the application. This can be due to various factors, such as network issues, timing problems, or resource limitations. Flaky tests can undermine confidence in your testing process, making it harder to trust the results.
By having a less strict way of describing what to test, QA.tech can handle most changes in an application, as long as the user still can reach their goal.
Requirement for a Realistic Environment:
For E2E tests to be meaningful, they need to run in an environment that closely mimics production. This means setting up databases, web servers, and other infrastructure components beforehand. Ensuring that the environment is properly configured can be time-consuming and resource-intensive. Particularly if you need to maintain it across multiple test runs.
QA.tech runs towards any environment that you already have, such as a staging or testing environment, making setup a breeze.
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We set out to make E2E testing accessible for everyone, by mitigating the hard and complex parts.
Get good E2E coverage right away
We scan your product, build a knowledge graph, and use the graph to generate tests that are tailor made for you, without any work needed from you
Less flakiness
By having our AI agent test your application, we don’t have to rely on deterministic instructions for the test, which are bound to fail as the application changes and evolves
Follow best practices
We have ingested countless websites as we have trained our model, and can help you follow best practices to improve your conversion, and customer experience.