Skip to content
3 Generations of Regression Testing. Definition & Use Cases | Loadmill
Regression Testing·

3 Generations of Regression Testing. Definition & Use Cases | Loadmill

Shachar Landshut
by Shachar Landshut
3 Generations of Regression Testing. Definition & Use Cases | Loadmill

Regression bugs take up developer time and energy and delay the delivery of new features to users. But in today’s world, customers expect software to be delivered fast while keeping a high-quality level. They also expect bugs to be fixed quickly and their software requests to be incorporated in product roadmaps. Regression testing can prevent these bugs and help development teams meet customer demands. 

Let’s take a look at the three generations of regression testing: manual, automated, and AI-driven, and see when it’s recommended to use each one. But first, let’s clarify what are regression bugs and testing.

What is Regression Testing?

Regression testing is the type of testing that is run to prevent regression bugs. Regression tests are run after changes are made to the software or when a new feature is added, to make sure these modifications did not negatively impact functionality or performance. Thus, developers gain confidence to build and release the software they’ve developed.

Regression tests can be either unit tests or integration tests, and they are usually a re-execution of test cases that have worked in the past.

What are Regression Bugs?

A regression bug is a bug that causes a feature to stop working correctly after it was already working. Regression bugs often occur as a result of a code or configuration change, like a system upgrade or system patching. This change could occur in the tested software, or in another, unrelated, software component.

Why is Regression Testing Important?

Finding regression bugs is a resource-heavy process, which can take a long time and requires many hours of developer manual work. Even a tiny code change can break any of the existing product features so many of them may need to be validated in every cycle. But by running regression tests in agile before committing and releasing, regression bugs - and the painful process of finding them - can be prevented. What are the Three Techniques of Regression Testing?

Over the years, regression tests have evolved. We can differentiate the types into roughly three generations:

  • Generation 1 - Manual Regression Testing

  • Generation 2 - Automated Regression Testing

  • Generation 3 - AI-driven Regression Testing

Let’s dive into each one.

Regression Testing Types

1st Generation - Manual Regression Testing

At first, developers started out with manual testing. This means that engineers had to define and execute tests to cover all of the possible user flows of the product themselves. The advantages of manual testing are mainly the abilities to:

  • Test new test cases that weren’t thought about previously, I.e exploratory testing

  • Run test types for components that are considered brittle, like in the case of UI tests - because the objects they test are changed frequently

  • Provide a quality description of success or failure, rather than a simple “failed-passed” result

However, manual testing is slow and is considered inefficient. Consider the following steps taken during a manual test:

  1. Manually list all updates to the product

  2. Determine which features might have been affected by these changes

  3. Identify software components to be included in the tests

  4. Create test cases

  5. Run the tests

  6. Monitor test results

  7. Create bug reports

  8. Fix your bugs

That’s a lot of work! To top it off, quite often test cases are repetitive and prone to errors. This is especially problematic for agile teams, which need to deliver quick product updates in short sprints and can’t move into “Code Freeze” mode before release.

2nd Generation - Automated Regression Testing

To answer the challenges of manual testing and to enable quick and efficient continuous regression testing, automation was introduced. Automated regression testing entails a test automation tool running the regression tests from your prebuilt testing suite, at a predetermined frequency. 

For example, running thousands of unit tests after every build. As a result, they can immediately check the impact of changes, to ensure new features, environment settings, or vulnerable code are not affected, without the developer having to lift a finger.

Despite all these advantages, automated regression testing does not offer full testing coverage, as the test plan will only cover the predetermined test cases. But what happens if a user suddenly decides to go through a different path that was not previously added to the regression testing suite?

3rd Generation - AI-driven Regression Testing

The most technologically advanced generation of regression testing is AI-driven regression testing. In this type of testing, tests are automatically created. But, instead of developers having to build test cases, scenarios are autonomously generated based on real user behavior. This ensures these tests are the most accurate and relevant and can directly impact the customer experience. At the same time, automation engineers are relieved of writing basic test cases and can perform more advanced tasks, like adding human insights or creating more sophisticated tests.

After creation, the tests are run after every build and success/failure is automatically updated in GitHub or any other code repository. AI helps ensure only the relevant tests for each code change are run.

Such testing is especially useful in the case of microservices, when it’s very hard for developers to build test cases, as they lack visibility into the architecture. Therefore, the use of AI-driven regression testing is expected to expand, alongside the accelerated adoption of distributed architecture. Over time, the levels of autonomy AI has will grow, with AI writing more and more tests, with less and less engineer supervision.

Summing Up: Advantages and Disadvantages of Regression Testing

Each type of testing has its own advantages and can be used in different use cases. Let’s take a look at each one.

Manual Regression Testing:


  • Enables exploratory testing

  • Enables testing of "brittle" components

  • Enables in-depth understanding of test success or failure


  • Slow

  • Boring

  • Inefficient

When to Use:

UI testing, sanity testing, occasionally to ensure nothing has been overlooked in the testing suite.

Automated Regression Testing:


  • Quick

  • Cost-effective

  • Frees up developers' time

  • Scalable

  • Integrates into the SDLC


  • Rigid

  • Requires setting up a testing suite

When to Use:

Unit testing, integration testing, when introducing new features, after every build, to shift left security

AI-driven Regression Testing:


  • Combines automation with exploratory testing

  • Covers real user test cases

  • Customer-oriented

  • Frees up developers' time

  • Scalable

  • Integrates into the SDLC

  • Provides visibility into microservices


  • Does not replace manual and automated testing completely (for now)

When to Use:

Continuously, after every build, after every release. To start automated AI-driven regression testing for free, click here.