20 February 2024

11 Min. Read

What is Regression Testing? Tools, Examples & Techniques

Fast Facts

Get a quick overview of this blog

Learn how regression tests can help you stay on top of your API testing game
Leverage HyperTest to catch any regressions beforehand before it turns into bugs
Discover essential tools such as HyperTest, Selenium and JUnit for effective Regression Testing.
Explore how Regression Testing ensures the continued functionality and stability of software systems.

Regression testing infuses confidence in the reliability of the software by systematically validating the unchanged portions of the software alongside newly added features. Regression testing is an integral part of Continuous Integration and Continuous Delivery (CI and CD) pipelines which aids in the rapid delivery of high-quality software products. Performing regression testing throughout the software development process safeguards against untoward consequences.

What is Regression Testing?

Regression testing is a software testing process that aims at ensuring new code changes do not negatively impact existing functionalities. The entire application or specific modules are retested to detect side effects due to code modifications. Regression testing guarantees that the previously developed and tested software remains intact and functions as expected after changes are incorporated.

The primary goal of regression testing is the identification and fixing of any bugs that may have been introduced during the development or modification phase.

This maintains overall integrity and stability of the software system. Regression testing is automated to expedite the testing cycle and ensure coverage of test cases. This facilitates swift execution of test scripts and detection of issues early in the software development cycle.

Why Regression Testing?

Regression testing is important in the software development lifecycle as it ensures the stability of a constantly changing system. The primary purpose of regression testing is to identify and rectify any unintended side effects or defects that may arise due to modifications in the codebase.

Regression testing provides a safety net for all the software evolutions, additions of new features, bug fixes and enhancements which impact existing functionalities, by systematically retesting the application and ensuring the software continues to meet its requirements.
By incorporating regression testing, development teams can catch issues early on so as to prevent the build up of hidden bugs that jeopardize the system. This maintains the quality of the software by ensuring that changes do not negatively impact previously established functionalities.
Automated regression testing also streamlines this process by allowing the swift and comprehensive validation of the entire codebase. Hence, regression testing is necessary and indispensable for the delivery of high-quality software products that not only meet user expectations but also adhere to specified standards.

Examples of Regression Testing

Regression testing is crucial in maintaining software quality and stability amid changes. It ensures that new code changes do not adversely affect existing functionality.

1. Software Upgrades

Scenario: Implementing a new version of software might introduce enhancements or new features. Regression testing is vital to confirm that these updates do not break existing functionalities.

Technical Strategy: Automate regression tests for critical workflows in the software. Use a continuous integration (CI) pipeline to run these tests against the upgraded version.

Example:

# Automated regression test for a login feature
def test_login_functionality():
    user_credentials = {"username": "user", "password": "password"}
    login_response = authenticate_user(user_credentials)
    assert login_response.status_code == 200
    assert "Welcome, user" in login_response.text

2. Bug Fixes

Scenario: After resolving bugs, it's essential to conduct regression testing to ensure the fixes haven't inadvertently impacted other functionalities.

Technical Strategy: Implement targeted regression tests around the fixed bugs and broader tests across the application to detect any unintended side effects.

Example:

# Regression test around a bug fix for payment processing
def test_payment_process_after_bug_fix():
    payment_details = {"amount": 100, "currency": "USD"}
    payment_response = process_payment(payment_details)
    assert payment_response.status_code == 200
    assert "Payment successful" in payment_response.text

3. Code Refactoring

Scenario: Refactoring code for performance or readability should not alter the application's behavior. Regression tests confirm that refactoring hasn't introduced errors.

Technical Strategy: Execute a comprehensive suite of regression tests covering the application's functionality to verify behavior remains consistent post-refactoring.

Example:

# Example test case for a feature after code refactoring
def test_feature_x_after_refactoring():
    input_data = {"key": "value"}
    feature_response = feature_x(input_data)
    assert feature_response.status_code == 200
    assert feature_response.json()["result"] == "expected outcome"

4. Integration of Modules

Scenario: Adding new modules or integrating third-party services can cause conflicts with existing code. Regression testing ensures seamless integration.

Technical Strategy: Design integration tests that mimic real-world usage of the combined modules, followed by regression tests to check for breakages in existing functionalities.

Example:

# Integration test for newly integrated module
def test_integration_with_new_module():
    result = new_module.functionality(existing_module.data)
    assert is_valid(result)

💡 Test Code with all Integration Points: See HyperTest in Action Now!

5. UI Changes

Scenario: UI updates, while primarily visual, can affect the functional aspects of the application, necessitating regression testing.

Technical Strategy: Use automated UI testing tools (like Selenium) to verify that UI changes do not disrupt the user's ability to interact with the application as expected.

Example:

# Selenium test for UI functionality after UI changes
from selenium import webdriver

driver = webdriver.Chrome()
driver.get("<http://application-url>")
login_button = driver.find_element_by_id("loginButton")
login_button.click()
# Verify login form is displayed
assert driver.find_element_by_id("loginForm").is_displayed()

6. Database Modifications

Scenario: Changes to the database schema or data structure require careful regression testing to ensure data integrity and application stability.

Technical Strategy: Implement tests that execute database operations (CRUD) and validate the application's ability to handle data correctly post-modification.

Example:

# Test for verifying database operations after schema modification
def test_database_operations():
    new_data = {"column1": "value1", "column2": "value2"}
    insert_response = insert_into_database(new_data)
    assert insert_response.success
    fetched_data = fetch_from_database(new_data["id"])
    assert fetched_data == new_data

7. Configuration Changes

Scenario: Adjusting configuration settings might have wide-ranging effects on the application's behavior and performance.

Technical Strategy: Apply regression testing to validate the application under different configurations, ensuring stability across various environments.

Example:

# Test for application behavior under different configuration
def test_application_with_new_configuration():
    apply_configuration("new_config")
    response = application_function()
    assert response.status_code == 200
    assert "Expected behavior" in response.text

8.Security Patching

Scenario: Security patches are crucial for addressing vulnerabilities but must be applied carefully to avoid introducing new issues.

Technical Strategy: After applying a security patch, conduct regression tests focused on security features and general application functionality to ensure no regressions.

Example:

# Test verifying application functionality post-security patch
def test_security_features_post_patch():
    secure_endpoint_response = access

_secure_endpoint()
    assert secure_endpoint_response.status_code == 403  # Expect unauthorized access to be blocked

In each of these scenarios, the goal is to implement targeted, comprehensive regression testing strategies that use automation to efficiently validate software quality and functionality. By incorporating these technical approaches and examples into your regression testing practices, you can significantly improve your software's reliability and performance amidst changes.

Quick Question

Are you planning to automate your API Testing?

Yes

What Are the Different Types of Regression Testing?

Different types of regression testing exist which cater to varying needs of the software development lifecycle. The choice of regression testing type depends on the scope and impact of changes, allowing testing and development teams to strike a balance between thorough validation and resource efficiency. The following are the types of regression testing.

1.Unit Regression Testing:

Isolated and focused testing on individual units of the software.
Validates that changes made to a specific unit do not introduce regressions in its functionality.
The efficiency of this lies in catching issues within a confined scope without testing the entire system.

2. Partial Regression Testing:

This involves testing a part of the entire application and focusing on modules and functionalities that are affected by recent changes.
The benefit of partial regression testing is that it saves time and resources especially when the modifications are localised.
Balances thorough testing with efficiency by targeting relevant areas impacted by recent updates.

3. Complete Regression Testing:

This involves regression testing of the entire application thereby validating all modules and functionalities.
It is essential when there are widespread changes that impact the software.
It ensures overall coverage even though it is time-consuming when compared to partial regression testing.

Regression Testing Techniques

Now that we know what the different types of regression testing are, let us focus on the techniques used for the same. Regression testing techniques offer flexibility and adaptability that allow development and testing teams to tailor their approach towards testing based on the nature of changes, project size and resource constraints.

Specific techniques are selected depending on the project’s requirements which, in turn, ensures a balance between validation and efficient use of testing resources. The following are the techniques teams use for regression testing:

1.Regression Test Selection:

It involves choosing a part of the test cases based on the impacted areas of recent changes.
Its main focus is on optimising testing efforts by selecting relevant tests for correct validation.

2. Test Case Prioritization:

This means that test cases are ranked based on criticality and likelihood of detecting defects.
This maximises efficiency as it tests high-priority cases first thereby allowing the early detection of regressions.

3. Re-test All:

This requires that the entire suite of test cases be run after each code modification.
This can be time-consuming for large projects but is ultimately an accurate means to ensure comprehensive validation.

4. Hybrid:

It combines various regression testing techniques like selective testing and prioritisation to optimise testing efforts.
It adapts to the specific needs of the project and thus, strikes a balance between thoroughness and efficiency.

5. Corrective Regression Testing:

The focus is on validating the measures applied to resolve the defects that have been identified.
This verifies that the added remedies do not create new issues or impact existing functionalities negatively.

6. Progressive Regression Testing:

This incorporates progressive testing as changes are made during the development process.
This allows for continuous validation and thus minimising the likelihood of accumulating regressions.

7. Selective Regression Testing:

Specific test cases are chosen based on the areas affected by recent changes.
Testing efforts are streamlined by targeting relevant functionalities in projects with limited resources.

8. Partial Regression Testing:

It involves testing only a subset of the entire application.
This proves it to be efficient in validating localized changes without the need for the entire system to be retested.

5 Top Regression Testing Tools in 2024

Regression testing is one of the most critical phases in software development, ensuring that modifications to code do not inadvertently introduce defects. Using advanced tools can not only significantly enhance the efficiency of regression testing processes but also the accuracy of the same.

We have covered both the free and the paid Regression Testing tools. The top 5 best performing Regression Testing Tools to consider for 2024 are:

HyperTest
Katalon
Postman
Selenium
testRigor

1. HyperTest - Regression Testing Tool:

HyperTest is a regression testing tool that is designed for modern web applications.
It offers automated testing capabilities, enabling developers and testers to efficiently validate software changes and identify potential regressions.
HyperTest auto-generates integration tests from production traffic, so you don't have to write single test cases to test your service integration. For more on how HyperTest can efficiently take care of your regression testing needs, visit their website here.

👉 Try HyperTest Now

2. Katalon - Regression Testing Tool:

Katalon is an automation tool that supports both web and mobile applications.
Its simplified interface makes regression testing very easy thereby enabling accessibility for both beginners and experienced testers.

Know About - Katalon Alternatives and Competitors

3. Postman - Regression Testing Tool:

While renowned for Application Programming Interface (API) testing, Postman also facilitates regression testing through its automation capabilities.
It allows testers and developers to create and run automated tests, ensuring the stability of APIs and related functionalities.

Know About - Postman Vs HyperTest - Which is More Powerful?

4. Selenium - Regression Testing Tool:

Selenium is a widely used open-source tool for web application testing.
Its support for various programming languages and browsers makes it a go-to choice for regression testing, providing a scalable solution for diverse projects.

5. testRigor - Regression Testing Tool:

testRigor employs artificial intelligence to automate regression testing.
It excels in adapting to changes in the application, providing an intelligent and efficient approach to regression testing.

Regression Testing With HyperTest

Imagine a scenario where a crucial financial calculation API, widely used across various services in a fintech application, receives an update.

This update inadvertently changes the data type expectation for a key input parameter from an integer (int) to a floating-point number (float).

Such a change, seemingly minor at the implementation level, has far-reaching implications for dependent services that are not designed to handle this new data type expectation.

The Breakdown

The API in question is essential for calculating user rewards based on their transaction amounts.

➡️Previously, the API expected transaction amounts to be sent as integers (e.g., 100 for $1.00, considering a simplified scenario where the smallest currency unit is integrated into the amount, avoiding the need for floating-point arithmetic).

➡️However, after the update, it starts expecting these amounts in a floating-point format to accommodate more precise calculations (e.g., 1.00 for $1.00).

➡️Dependent services, unaware of this change, continue to send transaction amounts as integers. The API, now expecting floats, misinterprets these integers, leading to incorrect reward calculations.

➡️ Some services might even fail to call the API successfully due to strict type checking, causing transaction processes to fail, which in turn leads to user frustration and trust issues.

➡️As these errors propagate, the application experiences increased failure rates, ultimately crashing due to the overwhelming number of incorrect data handling exceptions. This not only disrupts the service but also tarnishes the application's reputation due to the apparent unreliability and financial inaccuracies.

The Role of HyperTest in Preventing Regression Bugs

HyperTest, with its advanced regression testing capabilities, is designed to catch such regressions before they manifest as bugs or errors in the production environment, thus preventing potential downtime or crashes. Here's how HyperTest could prevent the scenario from unfolding:

Automated Regression Testing: HyperTest would automatically run a comprehensive suite of regression tests as soon as the API update is deployed in a testing or staging environment. These tests include verifying the data types of inputs and outputs to ensure they match expected specifications.
Data Type Validation: Specifically, HyperTest would have test cases that validate the type of data the API accepts. When the update changes the expected data type from int to float, HyperTest would flag this as a potential regression issue because the dependent services' test cases would fail, indicating they are sending integers instead of floats.

Immediate Feedback: Developers receive immediate feedback on the regression issue, highlighting the discrepancy between expected and actual data types. This enables a quick rollback or modification of the dependent services to accommodate the new data type requirement before any changes are deployed to production.
Continuous Integration and Deployment (CI/CD) Integration: Integrated into the CI/CD pipeline, HyperTest ensures that this validation happens automatically with every build. This integration means that no update goes into production without passing all regression tests, including those for data type compatibility.
Comprehensive Coverage: HyperTest provides comprehensive test coverage, ensuring that all aspects of the API and dependent services are tested, including data types, response codes, and business logic. This thorough approach catches issues that might not be immediately obvious, such as the downstream effects of a minor data type change.

By leveraging HyperTest's capabilities, the fintech application avoids the cascading failures that could lead to a crash and reputational damage. Instead of reacting to issues post-deployment, the development team proactively addresses potential problems, ensuring that updates enhance the application without introducing new risks. HyperTest thus plays a crucial role in maintaining software quality, reliability, and user trust, proving that effective regression testing is indispensable in modern software development workflows.

💡 Schedule a demo here to learn about this approach better

Conclusion

We now know how important regression testing is to software development and the stability required for applications during modifications. The various tools employed ensure that software is constantly being tested to detect unintended side effects thus safeguarding against existing functionalities being compromised. The examples of regression testing scenarios highlight why regression testing is so important and at the same time, versatile!

Embracing these practices and tools contributes to the overall success of the development lifecycle, ensuring the delivery of high-quality and resilient software products. If teams can follow best practices the correct way, there is no stopping what regression testing can achieve for the industry.

Please do visit HyperTest to learn more about the same.

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