Example scenario: automating regression tests for frequent releases
The team wants to prepare releases more frequently, but before each one it needs to repeat the same user journeys. Manual testing consumes a significant portion of its capacity, and the result arrives late. The goal is not to remove people from testing, but to move repeatable checks to automation and free up time for new and unforeseen risks.
Starting point
The web application or online store changes in short cycles. Before a release, the team verifies sign-in, search, ordering, payment, and other important flows. When the deadline gets shorter, so does the list of checks, or the team tests mainly what has changed.
A defect can also appear in a seemingly unrelated area. The team therefore has to choose between waiting longer for the release and taking a greater risk in production. If automated tests already exist, some of them may fail intermittently, which means that the results need repeated manual investigation.
How the situation can be addressed
1. Map the risk and the current time spent
First, list the scenarios being checked, how long they take, and the impact of a potential defect. Use this information to select the first journeys suitable for automation. They may include sign-in, ordering, or payment, but not automatically everything.
2. Prepare the conditions for stable tests
Tests need a stable way to find elements, their own data, and an environment in which they can safely complete the entire scenario. We describe these conditions in how to prepare a website for automated tests.
Repeated parts of the interface are separated from the scenarios themselves, for example with the Page Object Model or component objects. Large numbers of combinations can be checked at the API level where appropriate, because those tests are often faster and easier to diagnose.
3. Introduce tests gradually
The first small suite can run in CI/CD on agreed changes and regularly in the test environment. When a test fails, the team should receive enough information to make a decision, such as an error message and, depending on the configuration, a trace, screenshot, or video. More scenarios are added only after the results are stable and the team responds to them.
4. Measure the result
Compare the time spent on the manual check, the duration of the automated run, the number of intermittent failures, and the maintenance time. Only measurement will show whether feedback has shortened from days to hours or from hours to minutes. The same data helps determine what to automate next.
What to watch out for
An automated test can fail because of the application, the test, or the environment. The goal is therefore not to promise that every red result means a product defect, but to reduce ambiguous failures enough for the team to assess the result quickly. It is equally important to assign an owner for maintenance after every application change.
What users and the team gain
- Important journeys are checked in the same way in every agreed run.
- The result can arrive sooner, and the release does not have to wait for every repeated manual step.
- Testers have more time for new features, usability, and exploratory testing.
- The tests and their history remain in the repository and can be transferred to another team.
Next step
Measure which manual checks take the longest before a release and which protect against the greatest risk. If you would like to prepare a realistic pilot, contact us. We will propose the scope, execution method, and metrics for evaluating its value.