Regression testing
Automated regression testing
Regression suites do not die from running, they die from maintenance. Klarent's agents repair the suite as the app changes, so a full pass stays affordable every release.
The regression testing problem
Why regression suites get cut back
Broken before it runs
A share of the regression suite breaks on every deploy, from UI changes rather than real defects, before it can tell you anything.
Longer than the release window
Full runs take longer than the release cycle allows, so the suite runs late, partially, or not at all.
Flaky tests cost the most
Flaky tests cost more investigation time than real failures, and every false alarm makes the next red run easier to ignore.
Coverage quietly drops
So the suite shrinks, and test coverage quietly drops release by release, until regressions reach users.
Maintenance becomes the job
Test maintenance eats the time meant for new coverage, and the automation team spends each sprint repairing last sprint.
Failures without context
A red result with no evidence means someone has to reproduce the failure by hand before anyone can fix it.
Platform capabilities
How Klarent keeps a regression suite alive
Self-healing tests
When steps break because elements, IDs or locators changed, Klarent re-resolves and repairs them against the latest application flow.
Failure triage
Real regressions are separated from flaky tests and environment noise, so the team only investigates what matters.
Selective runs
Run only what a change actually touches for fast feedback, and keep the full regression suite for the release.
Parallel execution
Parallel execution with no concurrency cap, so a full-suite run fits inside the release window.
Trend reporting
Track pass rate across releases, and spot where the suite is getting weaker.
Evidence on every failure
Each run records executed steps with screenshots, the error message, and Playwright traces with console and network logs.
Building a regression suite that holds
What to automate first
Revenue and conversion paths
Sign-up, checkout and payment journeys, where a regression costs money the same day.
Recently changed areas
Features changed in the last two releases, where new regressions are most likely.
Integration points and fragile workflows
Third-party services, APIs and the workflows that have broken before.
What to leave to exploratory testing
One-off checks, fast-moving prototypes and judgement calls that a human explores better than a script.
Smoke, regression and full suite
What runs when
Set the gate on a small, stable smoke suite so pull requests stay fast, and let the larger suites run on a schedule or on the release candidate.
| Suite | When it runs | What it gates |
|---|---|---|
| Smoke suite | Every pull request | The merge. A failing critical path blocks it, everything else reports without blocking. |
| Regression suite | Nightly, and on every deploy to staging | Nothing by default. Failures are triaged the next morning, before they reach a release. |
| Full suite | On every release candidate | The release. It ships when the full pass is green or every failure is understood. |
Testing a mobile app? Mobile has its own release gates and device matrix. Mobile regression testing
Fits your release process
Regression testing automation in your pipeline
CI triggers
Trigger suites from GitHub, GitLab, Jenkins or Azure DevOps on every pull request or deploy.
Release gating
Failed critical tests block the merge or the release, and report the issue.
Results into Jira, Slack and Teams
Run summaries and failures reach the tools your team already works in.
Integrations
Fits into your existing stack
Connect to GitHub, Jira, Slack, and more - no reconfiguring your workflow.
Run a full regression pass against your app.
See Klarent run your regression suite in parallel, repair what the UI broke, and separate real failures from noise, in a live walkthrough on your application.
FAQs
Automated regression testing reruns your existing tests after every change to check that features which worked before still work. Instead of testers repeating the same checks by hand each release, the regression suite runs automatically from CI, on a schedule, or on demand.
A common pattern is a small smoke suite on every pull request, the regression suite nightly and on every deploy to staging, and the full suite on every release candidate.
Tests run in parallel with no cap on concurrency, so a full run takes roughly as long as the slowest test rather than the sum of all of them. As an example, ten tests that would take around 100 minutes by hand finish in 2 to 3 minutes.
Most breaks come from the UI changing, not the feature: renamed elements, new IDs or moved locators. Self-healing repairs those steps against the latest application flow, so the test keeps passing without a manual rewrite.
Start with revenue and conversion paths, then the areas changed in the last two releases, then integration points and workflows that have broken before. Leave one-off checks and fast-changing prototypes to exploratory testing.
Every run starts in a fresh, isolated environment, which removes a common source of flakiness. Failure triage separates real regressions from flaky tests and environment noise, and each failure comes with screenshots and traces so it can be diagnosed quickly.
Much less of it. Automation takes over the repeated checks every release needs, which frees testers for exploratory testing and judgement calls that automation does not cover well.
Smoke testing is a small, fast check that a build is not broken in its most critical paths, usually run on every pull request. Regression testing is broader, checking that everything which worked before still works, and usually runs nightly or before a release.