Regression Testing in Software Testing: 6 Types, a 7-Step Process, and Best Practices

Regression testing in software testing is the practice of re-running tests after a code change to confirm that features which already worked still work. Every bug fix, new feature, library upgrade, or configuration change can break something elsewhere in the application. Regression testing catches those side effects before your users do, which protects revenue, reputation, and release schedules.

Despite its importance, many teams treat regression testing as an afterthought, running a random handful of checks right before release. In this guide, we’ll explain what regression testing is, why it matters, the six main types, a practical seven-step regression testing process, how to decide what to automate, and the mistakes that make regression suites slow and unreliable.

What Is Regression Testing?

A “regression” happens when software that used to behave correctly stops doing so after a change. For example, a developer updates the tax calculation for one country, and suddenly discounts stop applying at checkout. Nobody touched the discount code directly, yet it broke because both features share a pricing function.

Regression testing exists to detect exactly this kind of problem. Instead of only testing the new change, the team re-runs a selected set of existing tests covering areas the change might affect. If those tests still pass, the team gains confidence that the release didn’t damage existing behavior.

Regression Testing vs Retesting

People often confuse these two terms, so it helps to separate them clearly.

In other words, retesting asks “did we fix it?” while regression testing asks “did we break anything else while fixing it?”

Why Regression Testing Matters

Modern software changes constantly. Teams ship updates weekly or even daily, and each update touches shared code, databases, and third-party services. Without regression testing, every release becomes a gamble.

The benefits show up in several ways:

• Fewer production incidents: Teams catch side effects before customers encounter them.
• Safer refactoring: Developers can clean up old code knowing tests will flag unintended changes.
• Faster releases: Automated suites replace days of manual checking with minutes or hours of test runs.
• Lower fix costs: Bugs found right after a change are easier to diagnose because the change is fresh and small.

This idea sits at the heart of continuous integration. As Martin Fowler explains in his widely cited article on continuous integration practices, a self-testing build that runs on every change lets teams find integration errors quickly, while only a small amount of code separates a working build from a broken one.

6 Types of Regression Testing

Not every change requires the same depth of testing. Choosing the right type keeps your effort proportional to the risk.

The Regression Testing Process: 7 Steps

A repeatable regression testing process prevents gaps and keeps the suite trustworthy over time. The following seven steps work for teams of most sizes.

1. Analyze the change. Review what changed in the code, configuration, or data. Identify which modules, APIs, and screens depend on that change.
2. Assess risk. Rank affected areas by business impact and likelihood of failure. Payment, login, and data-saving features usually rank highest.
3. Select test cases. Pull relevant tests from your suite. Always include a core “smoke” set covering critical user journeys, regardless of the change.
4. Update outdated tests. If expected behavior changed intentionally, update the affected tests so they reflect the new requirements.
5. Prepare the environment and data. Use an environment that closely matches production, with realistic and repeatable test data.
6. Execute and record results. Run automated tests first, then targeted manual checks. Log every failure with steps, screenshots, and environment details.
7. Triage, fix, and re-run. Classify failures as real defects, test issues, or environment problems. After fixes, re-run the affected tests and a smoke set before release.

Defects found during step seven should flow into your tracking system with clear ownership. Our guide to bug tracking and defect workflows covers how to keep those issues moving to resolution.

Manual vs Automated Regression Testing

Because regression tests repeat with every release, they’re among the best candidates for automation. Still, not every test should be automated.

What to Automate

• Stable, high-value user journeys such as sign-up, login, checkout, and data export.
• API endpoints and business rules with clear inputs and expected outputs.
• Calculations, validations, and permissions that must never change silently.
• Tests you run on every build or every release.

What to Keep Manual

• Visual and usability checks that need human judgment.
• Features still changing rapidly, where automated tests would break constantly.
• Rare, one-off scenarios where automation costs more than it saves.
• Exploratory testing that hunts for unexpected problems.

Popular open-source frameworks make browser-based regression automation more accessible than ever. For instance, Playwright’s official documentation shows how teams can run the same end-to-end tests across Chromium, Firefox, and WebKit from a single codebase. Meanwhile, unit and API tests usually run in the language-specific frameworks your developers already use.

Regression Testing Best Practices

The difference between a helpful regression suite and a frustrating one usually comes down to a few disciplined habits.

• Follow the test pyramid. Write many fast unit tests, a moderate number of API and integration tests, and a smaller set of slow UI tests.
• Run tests in CI. Trigger regression suites automatically on every merge so failures surface within minutes, not days.
• Fix flaky tests immediately. Tests that pass and fail randomly teach teams to ignore failures. Quarantine and repair them quickly.
• Keep test data under control. Seed known data before each run and clean up afterward, so results don’t depend on leftovers from earlier runs.
• Tag tests by priority and feature. Tags let you build fast selective suites without maintaining separate copies of tests.
• Review the suite regularly. Remove duplicate and obsolete tests, and add tests for every production bug so it can’t return.
• Track results over time. Monitor pass rates, run time, and escaped defects to see whether the suite is improving.

Regression Testing for Data and Infrastructure Changes

Code isn’t the only source of regressions. Database migrations, server upgrades, and third-party API changes can break features just as easily. Therefore, include data validation checks and integration tests whenever you change infrastructure. If you’re planning a database move, our guide to a safer production cutover shows where regression checks fit into the migration plan.

Common Regression Testing Mistakes

Watch out for these patterns, which quietly undermine even well-funded QA efforts:

• Testing only the changed feature. The whole point is to check what else might break.
• Letting the suite grow without pruning. Bloated suites run slowly, so teams start skipping them.
• Automating unstable features too early. Tests break with every UI tweak, wasting maintenance time.
• Ignoring environment differences. Tests that pass in a test environment but differ from production give false confidence.
• Treating failures as noise. If teams routinely re-run failed tests until they pass, real bugs will slip through.

Tools and Workflow Integration

A regression testing setup usually involves several connected tools: a test framework, a CI service that runs tests on each change, a test management tool or tagging scheme, and an issue tracker for defects. Many teams log failures directly into their project tracker. If your team uses Atlassian tools, our guide to Jira bug tracking explains how to structure that workflow.

When you work with an outside development partner, ask how they handle regression testing before you sign. Our article on choosing custom software development companies lists the QA questions worth asking.

Conclusion

Regression testing in software testing protects working features every time your code changes. By choosing the right type of regression testing, following a clear seven-step process, automating stable high-value tests, and keeping your suite fast and trustworthy, you can release more often with fewer surprises.

Start small. Identify your five most critical user journeys, automate tests for them, and run those tests on every change. Then grow the suite with every bug you fix.