Automated Regression Testing: A Complete Guide

Regression testing is crucial to any well-functioning CI/CD pipeline, but without automation, it takes up a lot of time and effort.

When you automate your regression tests to run on schedule, they constantly check your software for unintended side effects every time you make a change, which saves a lot of resources.

Let’s explore how automated regression testing can transform your software development process.

What is automated regression testing?

Automated regression testing is usually run after any new code enters the codebase, whether it’s a new feature, an enhancement, or a bug fix. Even small changes can unexpectedly affect other parts of the application, breaking existing functionality. To prevent this, teams need to verify the product’s behavior after every update. If issues slip through, they can surface during UAT or, worse, in production.

Manually retesting the entire system after each change is tedious, repetitive, and slow. In fast-moving agile environments, regression tests may need to run daily or even multiple times per day. To keep up, teams rely on automated tools that execute pre-written test cases with minimal human involvement.

Automated regression tests are designed to be run repeatedly across new builds. Running these tests multiple times ensures that every part of the application is validated and that existing functionality continues to work as intended.

In simple terms, it’s a safety net that maintains your software’s reliability by catching issues caused by new changes. This saves time, improves test coverage, and keeps the system stable.

Why automate regression testing?

• Faster feedback loops: Automated tests run immediately after code changes, catching issues early and reducing back-and-forth between developers and testers.
• Cost and time efficiency: Automation removes the repetitive burden of re-running tests manually, saving time and reducing long-term costs.
• Improved test coverage: Automated suites can run thousands of tests quickly, covering more scenarios, edge cases, and environments than manual testing.
• Consistency: Automated tests run the same way every time—no fatigue, no skipped steps—making results far more reliable.

Regression testing vs. retesting

• Regression testing checks whether recent code changes have affected existing features, while retesting verifies that a specific defect has been successfully fixed.
• Regression testing is broad, covering all related functionalities; retesting is narrow, focusing only on the failed test case.
• Regression tests are often automated and run frequently; retesting is usually manual and done after a bug fix.

Here's a brief comparison of regression testing vs retesting:

Step 2. Choose the right test cases to automate

We know what tests to run. However, not all tests should be automated. 100% automation testing is a myth.

Why is that? Because some test cases are just not suitable for automation. Either they are too complex or too dynamic to automate efficiently. Imagine automating a test case for your E-commerce homepage, which changes every day — sometimes every minute.

You're going to spend a lot of time updating the test to reflect those changes.

Instead, focus on stable, repetitive test cases that yield consistent results across multiple runs. For example, test scenarios like form submissions, login processes, and backend calculations are typically stable and ideal for automation.

📝 Read More: Top Test Cases For Login Page To Consider

Of course, there are certain scenarios where human intuition, creativity, and judgment are irreplaceable. Exploratory testing is a good example. Only after doing exploratory testing can you start test automation.

Step 3. Choose the right tools and frameworks

To automate regression tests, you have two approaches:

1. Build your own test automation framework
2. Use an automation testing tool

Building your own test automation framework means creating a customized system that defines how tests are structured, executed, reported, and maintained. Instead of relying on a vendor’s architecture, your team builds everything from the ground up — your own libraries, utilities, helper functions, and the logic powering your test suites.

You also manage environment setup and teardown, determine how tests run in CI/CD, implement reporting and logging, and choose the design patterns (POM, Screenplay, BDD). As the product grows, the framework must evolve with it, so ongoing maintenance becomes part of the workload.

Pros of building your own framework include:

• High levels of customization
• A workflow tailored to your domain and architecture
• Long-term flexibility and control

But the tradeoffs are real:

• Significant time and engineering investment
• Continuous maintenance requirements
• A slower path to initial value

This approach is ideal for teams with strong engineering capacity, a complex product, or long-term scalability needs.

The second path is adopting an out-of-the-box regression test automation tool. These solutions come with core capabilities already built and optimized: test authoring interfaces, automated execution engines, reporting dashboards, pipeline integrations, and support for multiple testing types (UI, API, mobile, load, depending on the platform). Many also include low-code features or record-and-playback, and often offer built-in mechanisms to adapt to application changes, reducing maintenance effort.

Advantages of this approach include:

• Faster onboarding and quicker time-to-value
• Lower engineering overhead
• Easier contributions from non-technical testers
• Ongoing updates, documentation, and vendor support

However, the limitations are worth noting:

• Less flexibility than a custom-built framework
• Potential fit issues for highly specialized use cases
• Licensing and scaling costs
• Limited extensibility in some tools

This route works best for teams that want immediate productivity, have fewer engineering resources, or need to empower manual testers to contribute quickly.

Step 4. Run tests and review results

With your test cases ready, it’s time for execution! For automated regression testing, there are several execution strategies:

• Batch Execution: You can group multiple test cases and execute them simultaneously. These “test suites” typically contain test cases with similar characteristics.
• Scheduled Execution: With a test case management system, you can schedule tests to run at set times—ideal for automated regression cycles.
• CI Integration: Test cases run automatically inside your CI/CD pipeline. Each new build triggers execution, quickly revealing new defects.

📚 Read More: How To Build a Good Regression Test Suite?

So we know what to execute and how to execute. Now we need to figure out where to execute:

The challenge here is that you may want to test on many environments, but company resources may not support them all. QA teams typically have two options when configuring test environments:

1. Option 1: Invest in real physical devices. These offer the highest level of realism, especially for device-specific scenarios like battery performance and real-world usage. However, it can be costly because QA teams need a broad range of devices for proper test coverage.
2. Option 2: Start testing in the cloud. Numerous cloud-hosted testing environments are available on demand, allowing teams to test across any browser, device, or OS at scale—without maintaining physical hardware. Katalon TestCloud is an example of a cloud-based testing solution.

📚 Read More: Emulator vs Simulator vs Real Device: A Comparison

Best automated regression testing tools

Many automated regression testing tools help teams design test cases, execute them across environments, integrate with CI/CD pipelines, and generate detailed reports. With support for parallel execution, these platforms can dramatically reduce test time and improve overall efficiency.

Some widely used tools include:

• Katalon: A unified automation platform for web, API, mobile, and desktop testing. It offers low-code scripting, test management, analytics dashboards, and seamless CI/CD integration—ideal for teams wanting rapid automation without heavy framework development.
• Playwright: A modern end-to-end testing framework supporting Chromium, Firefox, WebKit, and mobile emulation. Known for speed, reliability, auto-waiting, and strong parallel execution—excellent for cross-browser regression testing.
• Cypress: A JavaScript-based testing tool designed for modern web apps. It runs in the browser, delivering fast execution and strong debugging. Perfect for frontend teams using React, Vue, or Angular.
• JUnit / NUnit: Widely used in Java and .NET ecosystems for backend regression suites, strong CI/CD integration, and parameterized testing.
• Postman: Useful not only for API exploration but also for automated API regression tests. Collections can run via CLI or CI pipelines for faster, more reliable API regression workflows.
• GitHub Actions / GitLab CI: While not testing tools themselves, they play a crucial role in orchestrating and scheduling regression test runs across environments. They ensure consistency by running tests automatically with every commit.

Best practices for automated regression testing

Now that we’ve walked through the essentials of automated regression testing, it’s worth reviewing a few best practices that will strengthen your test suite and keep it reliable over time.

• Update Regression Test Cases: Continuously refine and update your regression suite to reflect the latest changes in the application. Outdated tests lead to blind spots.
• Categorize Your Tests: Group regression tests based on application behavior or functionality. When a test fails, clear categorization helps pinpoint where the issue lies and speeds up investigation for the development team.
• Re-run Passed Test Cases: In an agile environment, even previously successful tests should be executed regularly to verify that new changes haven’t introduced unexpected side effects.
• Review Test Reports Carefully: Even with daily automated runs, make time to analyze reports thoroughly. This ensures that no minor defects slip through unnoticed.

Regression testing is a cornerstone of the software development lifecycle, and automation is essential to maximize its impact. With fast releases and growing user expectations, automated regression testing ensures quicker cycles and a higher-quality product.

Why Katalon for automated regression testing?

Katalon is one of the strongest platforms for automated regression testing because it brings creation, execution, analytics, and maintenance into one unified ecosystem. Instead of stitching together separate tools for web, mobile, API, and desktop testing, Katalon provides an end-to-end workflow designed to keep regression suites stable, scalable, and easy to maintain.

The platform fits both technical and non-technical roles. Testers can build tests codelessly, while engineers can extend logic with scripts. This flexibility helps teams accelerate automation without compromising control.

Why Katalon for automated regression testing

• Cross-platform coverage: Run regression tests across web UI, mobile, API, and desktop.
• Stable, maintainable objects: Built-in object management reduces flaky tests and locator issues.
• Run tests anywhere: Execute locally, remotely, or at scale using TestCloud’s 3,000+ environments.
• Parallel execution: Speed up regression cycles using Katalon Runtime Engine.
• CI/CD ready: Integrates with GitHub Actions, Jenkins, Azure DevOps, Bitbucket, and more.
• Faster debugging: Screenshots, logs, videos, and structured reports help analyze failures quickly.

AI-powered features that strengthen regression suites

• Self-healing locators: AI stabilizes tests when UI changes break selectors.
• TrueTest for AI-generated regression tests: TrueTest analyzes real production usage and automatically generates regression flows.
• AI analytics in TestOps: Identify flaky tests, hidden risks, and repeated failure patterns.

TestCloud: On-demand execution without infrastructure overhead

• 3,000+ real-world environments: Browsers, devices, OS combinations.
• Parallel execution: Reduce runtime for even large regression suites.
• Seamless workflow: Trigger cloud runs directly from Studio or TestOps.

Katalon provides one of the broadest and most scalable ecosystems for automated regression testing—ideal for teams that need fast execution, reliable maintenance, and full visibility across the testing lifecycle.

📝 Ready to see how Katalon powers regression testing at scale? Request a personalized demo.