What is Regression Testing? Definition, Tools, Examples

Regression testing is the process of re-running existing tests after making code changes to ensure previously working functionality remains intact.

As modern applications grow more complex and interconnected, even a small update can create unexpected side effects across the system. Regression testing verifies that updates do not break existing features. A defect found during this process is known as a regression.

Examples of Regression Testing

Imagine you're testing an e-commerce application called VeryGoodEcommerce. Its current features include:

• Product browsing
• Search functionality
• Price calculation
• Payment processing
• Inventory updates

The development team introduces a new feature: applying discount codes at checkout. While it’s exciting, it may interact unexpectedly with existing functionality.

What if the discount logic affects product browsing or price calculation? Regression testing helps confirm that none of the five existing features are negatively impacted by the new discount feature. If any functionality breaks, it's a regression and the development team must fix it before release.

Benefits of Regression Testing

• Prevents cascading failures: Even minor code changes can create ripple effects across core features. Regression testing catches these early.
• Aligns with Agile workflows: Continuous iteration and testing make regression testing a natural fit within Agile development.
• Supports CI/CD pipelines: Automated regression tests ensure each integration is stable, making them essential in modern CI/CD processes.

One day, the dev team decided to add a new feature that allows users to apply discount codes at checkout. It's a fascinating feature, and beta users love it.

However, we can never know how that shiny new feature interacts with the current features.

What if it breaks the Product browsing? What if it breaks the Price calculation? 

That is why regression testing is needed. Instead of testing the new feature, you run tests for the five existing features to make sure that the new Discount feature didn't negatively affect them.

If the discount feature affects some feature (for example, price calculation), we call that a regression. The dev team is immediately informed of the issue for immediate troubleshooting. 

If the discount feature does not negatively affect anything, there is no regression, and everyone is happy. The new feature is then rolled out for users to enjoy.

Benefits of regression testing

• Prevents Domino Effect on Key Functions: Even minor modifications in the code can cause a rippling effect across the entire product’s key functionalities, and you need regression testing to detect these issues early.
• Aligns with Agile Methodology: Regression testing is all about iterating, integrating, and testing new code, and Agile is all about that. Their nature aligns with each other so seamlessly, making regression testing a part of Agile culture itself.
• Supports CI/CD Pipelines: Similar to Agile, CI/CD relies on running automated tests to ensure that new code integrations are continuously tested, which makes regression testing an integral part of it.

📚 Read More: Regression Testing in Agile: A Complete Guide

Challenges of Regression Testing

1. Time-consuming: every time you add or adjust a feature, you need to re-test existing functionality. In large or complex projects, a small change can lead to extensive testing. Without proper automation, regression testing becomes a major time sink and QA can turn into a bottleneck.
2. Test suite maintenance: as your application evolves, so does your regression suite. Keeping tests updated requires adding new cases, removing outdated ones, and modifying existing tests—especially UI tests, which frequently change.
3. Risk of overlooking bugs: under tight release timelines, it’s easy to miss smaller components. Features that worked flawlessly before can suddenly break. The more complex the system becomes, the higher the risk of hidden bugs slipping through.

When Is Regression Testing Done?

Regression testing is typically performed when:

• A new requirement is added to an existing feature
• A new feature or functionality is introduced
• A defect is fixed
• Code optimizations are made for better performance
• Patch fixes are applied
• A new software version is released
• User Interface changes occur
• Configuration changes are implemented
• A new third-party system is integrated

Retesting vs Regression Testing

• Retesting: re-running a test that previously failed to verify that the reported defect has been successfully fixed.
• Regression testing: validating that recent changes haven’t introduced new defects elsewhere in the system and that existing functionality remains stable.

In simpler terms:

• Retesting = “Did we fix the problem?”
• Regression Testing = “Did the fix cause new problems?”

Regression Testing vs. New Feature Testing

You can think of new feature testing as the opposite of regression testing:

• Regression testing checks existing features.
• New feature testing checks newly added features.

Together, they ensure quality across the entire application.

How to Do Regression Testing

1. Detect Source Code Changes

First, identify what changed and where. Common reasons include:

• Bug fixes
• New features
• Enhancements
• Configuration changes

2. Prioritize Impacted Areas and Test Cases

Not all changes carry the same level of risk. Prioritizing ensures you focus on the components most likely to break, especially critical or heavily modified areas.

Consider:

• Scope of code change
• Business criticality
• Frequency of use
• Historical defect density
• Interdependency
• User feedback
• Pain points

📚 Read More: How to Build a Regression Test Plan?

3. Determine entry point and exit point

This step is crucial because deciding when to start regression testing ensures that the environment is ready, the codebase is stable, and the test objectives are well-defined. Common entry points for this are:

• Build passes smoke testing.
• All development tasks and bug fixes related to the current release are complete.
• The test environment is fully set up and mirrors production.
• Test data is available and ready to be used.
• Regression test cases are prepared and prioritized.

Exit points, on the other hand, defines when testing can be considered complete. This ensures that sufficient testing has been done to meet quality standards before the software is released or moved to the next phase.

4. Categorize regression test cases

In this step, we deep-dive into the plan formulated in step 3 and categorize them by several factors:

• Manual vs automated regression tests: For ad-hoc or non-repetitive test cases, manual testing and human evaluation still make the most sense. Anything that involves the same series of test steps, over and over again, should be automated. Due to its highly repetitive nature, regression test is the perfect candidate for automation testing.
• Critical vs non-critical features: evaluate test cases based on urgency and significance and assign them a value of importance (high, medium, low). Other factors can also be brought into consideration based on business requirements.
• Testing types: each testing type calls for different setup, tools, and environment, so classifying test cases by type (for example functional/non-functional tests) can give the team better control over the testing activities.

📚 Read More: 10 Best Practices for Automated Regression Testing

5. Test environment preparation

Having test environments at hand at all times is important for frequent regression testing.

As new code is being developed constantly, environments need to be stable and ready-to-test to not interfere with the planned testing schedule. In addition, poor environment setup can give tests more reason to fail, missed defects and false positives/negatives.

📚 Read More: How to Set Up Test Environments

6. Schedule and execute tests

At this stage, all test cases are ready for execution. Teams can schedule test cases to run based on the test plan. Certain test cases can even be scheduled to run periodically in intervals over the entire development cycle. Time-based test execution allows teams to have greater quality control over the constant changes of their application.

📚 Read More: Test execution: A Complete Guide

7. Measure regression testing success

This stage gives important insights for future test runs. Comprehensive analytics generated from test results enable QA managers and other key stakeholders to quantify testing efficiency, assess resource utilization, and measure the effectiveness of the testing strategy.

Here is how a test report may look like. In Katalon TestOps, after running regression test suites, QA teams can access the dashboard with rich insights about the effectiveness of that test run.

Should regression testing be automated?

Yes, regression testing should be automated. Here's why:

• Regression testing fits all of the criteria for automation: it is repetitive, high-volume, and predictable. Manual regression testing is just tedious and not scalable at all.
• Automated regression testing supports Agile and CI/CD workflow: regression testing is a backbone of continuous testing. Without automation, your CI/CD pipeline is half-baked. Automated regression tests act as safety nets, catching bugs early before they snowball into production incidents or broken features.
  Automated regression testing opens up the gate to scale QA: Modern software development is fast, iterative, and CI/CD-driven. You might deploy daily or hourly. You simply cannot manually re-run hundreds or thousands of test cases every time. Automated regression tests can run in minutes across browsers, OSes, and devices (while you sleep).

However, sometimes manual regression testing still makes sense:

• Exploratory testing: When intuition, curiosity, and user empathy are needed.
• UI/UX validation: Human eyes catch layout glitches and visual regressions better.
• Highly dynamic interfaces: When the cost of automation maintenance outweighs the benefits.
• Short-lived features: Skip automation if the feature is temporary or will be deprecated soon.

📚 Read More: Manual Regression Testing vs. Automated Regression Testing

How to balance regression testing and new feature testing?

Let's meet Alex Martins, a veteran with 20+ years in software quality and automation across Fortune 500 companies. He shares how to automate regression tests when teams spend most resources on new feature testing:

How to automate regression tests?

Step 1: Know what you need to test

Focus on the parts of your app that break often or are mission-critical—like checkout flows in e-commerce. Use code coverage, bug history, and experience. Don’t test everything blindly.

Step 2: Pick the right regression test cases

Not all tests should be automated. Prioritize tests that are:

• Repetitive
• Stable
• High-impact

Examples: login flows, form submissions, backend calculations. Leave unpredictable or exploratory scenarios to humans.

To choose which test cases to automate, use a Test Case Selection Matrix — a scoring system that evaluates test cases based on five key factors:

• Run Frequency – how often the test is executed
• Stability – how consistently it behaves across builds
• Business Criticality – importance to users or revenue
• Reusability – shared logic with other tests
• Manual Effort – how painful or time-consuming it is manually

Here's how to use the matrix:

• List the factors you consider worth automating
• Score each factor from 0 to 1
• Sum the total (max = 5)
• Set a cutoff (e.g., 3.5+ = automate)

Use this during backlog grooming, test planning, or automation roadmap reviews to target high-value tests.

Example:

You can adjust weighting or scoring based on your team's priorities.

Step 3: Choose your tools

You have two paths:

• Build your own automation framework
• Use off-the-shelf tools (e.g., Katalon, Selenium)

Choose based on skills, timeline, and long-term strategy.

📝 Here's a curated list of the best automated regression testing tools

Step 4: Run your tests smartly

There are three common ways to run automated tests:

• Batch runs: Group tests by similarity.
• Scheduled runs: Run tests on a timer (e.g., nightly).
• CI/CD runs: Trigger tests automatically on each code change.

Choose where to run them: local machines, real devices, cloud platforms, or headless browsers. If you don’t have devices, use cloud testing services like Katalon TestCloud.

Regression testing techniques

1. Retest all

This technique involves re-running the entire test suite to ensure recent changes have not introduced new defects.

While reliable, it is expensive and time-consuming, making it impractical for large applications with frequent updates.

2. Regression test selection

This method selects a subset of test cases most relevant to the modified code, balancing cost and efficiency by focusing only on affected functionalities.

3. Test case prioritization

This technique ranks test cases by importance and likelihood of detecting critical defects, executing high-priority cases first.

Types of prioritization:

• General prioritization: Focuses on test cases valuable across multiple software versions.
• Version-specific prioritization: Targets cases relevant to the current release.

4. Hybrid regression testing

A combination of test selection and prioritization—picking the most important tests and running them in priority order.

Best practices of regression testing

1. Prioritize test cases: Focus on critical functionalities, high-risk areas, and recently modified components.
2. Automate where possible: Manual regression testing is slow and error-prone. Automate repetitive and high-impact tests to improve speed and accuracy.
3. Maintain your test suite: Update test cases regularly, remove outdated ones, and ensure coverage stays relevant. See tips on building an effective regression test suite.
4. Use continuous testing in CI/CD: Integrate regression tests into your CI/CD pipeline to catch issues early and reduce release risks.
5. Parallel testing: Running tests across multiple environments and devices reduces test execution time. Learn more about parallel testing.

Top regression testing tools and frameworks

Manual regression testing is tedious and inefficient. Using a regression testing tool enables you to create automated suites and run them in batches whenever a new build is available.

1. Katalon

Katalon helps QA teams automate regression tests for web, API, and mobile apps.

With a Katalon license, QA and automation testers can:

1. Use pre-built automation frameworks without starting from scratch.
2. Write test cases in Java/Groovy with the Page Object Model, or use keywords from the Keyword Library. Create custom keywords as needed and plug them into the IDE.
3. Execute regression tests locally, in the cloud, or remotely through TestCloud.
4. Manage and schedule executions in Katalon TestOps, including Jira integration for manual testing workflows.
5. Integrate Katalon into the CI/CD pipeline for parallel testing.

2. Selenium

Selenium is widely used for regression and web application testing thanks to its flexibility and compatibility with major browsers and operating systems.

Key features:

• Selenium Grid: Enables parallel testing across multiple machines.
• Selenium IDE: A record-and-playback tool with export options to frameworks like JUnit.
• Selenium WebDriver: Provides precise browser control for click actions, form submissions, file uploads, and more.

Selenium’s effectiveness depends heavily on coding skills—experienced testers can maximize its power, while less technical users may struggle.

📝 Read More: Katalon vs Selenium: A Detailed Comparison

3. Playwright

Playwright is a modern end-to-end testing framework known for its speed and versatility across JavaScript, TypeScript, Python, C#, and Java. It’s widely considered a strong alternative to Selenium and Cypress.

Highlights:

• Runs seamlessly across Chromium, Firefox, and WebKit with much faster execution than Selenium. Supports both web automation and API testing.
• Includes auto-waiting, screenshots, tracing, and a codegen tool for recording interactions and generating test code—ideal for fast productivity.
• Official bindings available for JavaScript/TypeScript, Python, Java, and .NET. TypeScript offers the richest documentation, but other languages work reliably as well.
• Built-in parallel execution and process-level test isolation with no need for external tools—a major advantage over Cypress for scaling large test suites.
• Auto-waiting minimizes the need for manual sleeps or explicit waits.
• Engineered for modern web apps and works smoothly with GitLab, Azure, Docker, and WSL. Non-TypeScript setups may require slightly more configuration.

Conclusion

Regression testing plays a critical role in improving product quality and user experience. The right tools help detect defects early and maintain system stability.

With Katalon, you can create regression tests in no-code, low-code, or full-code modes for maximum flexibility, then schedule and execute them across environments.