Regression testing is indeed one of the most time-consuming part of software testing: repetitive, tedious, and requiring high volume of executions.
And yet, you can't ignore regression testing. It is the guardrail preventing bugs from slipping into production. But if you don't try to reduce the time it takes to do regression testing, it becomes counter-productive, very soon.
That's why we have compiled five actionable strategies for your QA teams to speed up regression testing and achieve faster time-to-market.
Regression testing is the practice of re-executing test cases to verify that recent code changes haven't adversely impacted existing functionality.
As modern applications become increasingly complex and interconnected, even a small update can unintentionally affect other parts of the system. That's why, whenever the codebase is modified, regression tests are run to confirm that existing features still work as expected and no new issues have been introduced.
A bug discovered during this process is known as a regression.
The first and foremost action is to implement automation testing. Put simply, it is about writing automation scripts and schedule them to run on certain conditions (code push, new release, etc.)
However, automation testing must be done strategically:
Start by automating high-priority test cases, especially those covering critical functionality or areas with frequent code changes. Here's a guide on how to select test cases for automation.
Focus first on smoke and sanity tests, and API-level automation, which are faster and more stable than brittle UI tests.
Use test case tagging and prioritization to create subsets of tests that target the most important scenarios for quick validation.
Leverage parallel execution across containers, VMs, or cloud grids to reduce total test execution time.
Implement headless browser testing to speed up UI test runs by eliminating the rendering overhead.
đź’ˇ Tip: Try to find the most time-consuming tests and explore the possibility to convert them into automation.
If you already established some level of automation in your testing process, and still want to reduce testing time, it's a good idea to conduct a comprehensive test suite review to eliminate tech debt. Sometimes QA teams just run every single tests when it's not actually required.
Here are some items for you to do:
For every test case, ask: "What’s the risk if this breaks and we don’t catch it?" If the risk is low (e.g., cosmetic UI alignment or stable legacy features), it may be safe to skip the test in regression.
Sometimes certain tests may have already been validated indirectly by others. For example, if you have a test that completes checkout, it already includes the login step, so a separate login “happy path” test might be unnecessary. That's where you should optimize. Consider consolidating overlapping test flows into single, broader test cases when possible.
You can go even more granular and optimize execution time for individual test cases:
Treat regression tests as living assets with a defined lifecycle. Instead of letting your test suite grow indefinitely (which slows execution and increases maintenance), introduce a review-and-retire policy:
Track how many times each test case or test suite has been executed.
Set a threshold (e.g., after 10+ consecutive passes over several cycles).
If a test hasn't caught any issues and its coverage is already addressed elsewhere, review and consider retiring it.
You don't have to throw those tests away. They can be:
Archived temporarily (to be reactivated later if needed),
Merged into broader test flows,
Or replaced by lighter-weight checks (e.g., API or unit test).
This approach keeps your regression suite lean, relevant, and faster to run, while maintaining confidence in coverage.
đź“š Further reading: How to build an effective regression test suite?
Cloud-based device farms offer you powerful infrastructure to test across multiple real or virtual devices in parallel, so that you don't need to invest into real physical devices to do cross-browser and cross-platform regression testing. This is especially useful for mobile or web-heavy applications.
When to use it:
You’re releasing on both iOS and Android, and want to validate on multiple device models.
You need to test across legacy browsers or a matrix of browser/OS combinations (e.g., Chrome 122 on Windows 11 vs. Safari 15 on macOS Monterey).
You want to parallelize without scaling your local or on-premise infrastructure.
A full regression suite that takes 5–6 hours locally can often be reduced to under 1 hour using device farms with sufficient parallelism.
đź“š Further reading: Emulator vs Simulator vs Read Device: A comparison
Parallel test execution, also known as multithreaded execution, involves splitting your test suite across multiple threads so that tests run simultaneously instead of sequentially.
Parallelization is actually really simple, since most modern test frameworks support parallelization:
You can combine this with CI runners to further scale execution (e.g., split tests across agents in GitHub Actions or GitLab CI).
With Katalon, you can easily create regression test cases for web, mobile, and API thanks to our pre-built frameworks (including keyword-driven testing, data-driven testing, BDD, and more). They help you get started quickly, easily.
Here are some things you can do with the entire Katalon suite: