What is regression testing?

Regression testing is typically conducted after bug fixes are implemented, and it involves re-running tests to ensure features function as expected after new code is added.

One part of regression testing that makes it unique is the way it freely floats across all the different stages of software development testing. Regression testing can be conducted anytime you want or need to go back a step and make sure that the new code being introduced isn’t harming overall functionality and workflow efficiency.

Any organization whose computer code receives consistent updates probably needs to implement regression testing methods. Code updates are so pervasive across the board that it’s simply not possible to get an accurate total number with any reliability.

However, because of technologies like artificial intelligence (AI) and the continuous integrations/continuous delivery (CI/CD) pipeline, many enterprises are increasing the frequency of code changes, with some outfits making daily updates. That can add up to a lot of regression testing.

One key area where regression testing occupies center stage is during quality assurance (QA) efforts. The missions of regression testing and QA teams are remarkably similar—to optimize the user experience and deliver high-quality data and the most secure software possible.

The only difference is how much of the total picture each looks at. Regression testing uses a more precise scope to focus on changes recently made, while QA evaluates the entire system and its workings.

Regression testing techniques function as a backstop against code changes that lack compatibility with the system hosting them. It’s important to have such measures in place to keep system operation optimized.

In regression testing, this sequence of steps (or one nearly like it) is usually followed:

1. Introduce a code change: Add new code, modify existing code or optimize current functionality within the source code.
2. Consider possible impacts: Analyze the software application to identify areas potentially affected by the new changes.
3. Choose test cases: The DevOps team engages in test selection based on test cases within the regression test suite—focusing especially on those covering critical functionalities. They can include unit tests (for individual modules), functional tests (to verify operations) or integration tests (to ensure components work together).
4. Prioritize test cases: When multiple test cases are selected, the team undergoes test case prioritization to organize them based on importance and potential impact.
5. Run test cases: Execute tests manually or use automated regression testing tools. Regardless of the approach (for example, manual testing versus automated testing), rely on test scripts—structured templates that guide tester actions.
6. Report and analyze test results: Review the test outcomes and supporting data. If tests uncover bugs or failures, notify the development team promptly.
7. Make fixes and retest cases: Developers apply the necessary fixes to the existing test cases and retest the previously flagged issues to confirm resolution.
8. Repeat the entire process as needed: Continue the regression testing cycle as many times as necessary to ensure that the web application performs as intended.

For a topic that appears straightforward, there are a broad number of regression testing techniques in use. Each puts its own distinctive spin on regression testing.

As its name implies, this form of regression testing concentrates on the components or modules (or “units”) that make up a system, and whether errors have been introduced into that individual unit.

Example: Developers might decide to add a “Forgot password” feature to a website. A unit regression test would check to make sure that the original login mechanism continues to work as intended, despite the additional function.

When the goal is to find out whether recent changes have impacted only a subset of the updated system, partial regression testing is used to detect that subset and perform suitable diagnostics.

Example: Let’s say that a website is integrating a new payment gateway. Partial regression testing might evaluate only a portion of a new functionality and how it’s dedicated, leaving more unrelated features to go untested.

At other times, more comprehensive testing is needed, like following major code changes. Complete regression testing involves retesting the whole system or application to ensure ongoing functionality.

Example: The developers of a website decide to include a gallery of selected products. Once created, the company performs complete regression testing on the functionality of the new gallery and all existing test cases, which all need to be re-run.

Selective regression testing introduces a predictive element into regression testing. In it, test cases from the test suite are selected based on the testers’ belief that those areas are going to receive impacts from code changes made.

Example: Developers of a mobile application might discover they need to integrate and update some aspects of the user interface. In such an instance, the developers might employ selective regression testing to ensure the ongoing stability of the user interface.

A kind of mixed approach to testing evaluates both new features and existing features. Progressive regression testing checks each to detect bugs introduced through new functionality.

Example: Whenever an organization releases a new update to an existing software product, the company typically engages in progressive regression testing beforehand to ensure that the functionality of the latest update continues to reflect that exhibited by the series.

Ensuring data consistency is the point of corrective regression testing. Test cases are re-run to see whether similar test results occur. Corrective regression testing is often conducted when no changes have been made to the codebase.

Example: New features aren’t always what’s being added to software. Sometimes changes are introduced to refine the code and make it run better. Corrective regression testing is used in cases when code is refactored to make certain refactoring isn’t introducing code errors.

Retest-all regression testing is considered postfinal testing. It involves development teams running tests on all the regression test cases that have already been cleared, just to make sure that everything works together harmoniously.

Example: Retest-all regression testing is often used for checking the changes that can accompany major architectural shifts in software. For example, a financial app that adopts a new framework that represents a substantial change in operation.

The types of testing discussed can be time-consuming, which is why automated testing tools are often brought in to accelerate the process. The speed of test execution gets ramped up, even when large systems are involved.

Example: Automated regression testing can be used following backend updates to determine whether application programming interface (API) endpoints continue to generate correct data and responses, signifying correct overall operation.

Certain test scenarios require human understanding, and that’s where manual regression testing is conducted. It’s understood that manual testing typically requires more time to perform due to the special sensitivity that informs the work.

Example: Websites need to look both pleasing and comparable on various platforms. With the use of manual regression testing, you can check a website’s responsiveness following the making of layout changes.

This regression testing leverages Selenium, an open source web automation framework. Selenium regression testing enhances software stability by detecting regressions early and ensuring new changes don’t derail existing code. It’s especially useful in situations with constant updates, like continuous integration.

Example: A system for booking airline reservations adds a new piece of functionality that enables debit card payments in addition to the credit card payments previously allowed. Selenium can verify that the flow of credit card payments continues to operate as expected.

Software quality is judged according to several variables existing apart from the software development lifecycle (SDLC). Nonfunctional regression testing seeks to validate the presence of high-quality software that’s secure to use and that supports a good user experience.

Example: A website‘s developers add new features, then want to determine how the new functionality impacts operating speeds. Nonfunctional regression testing checks the loading times. If those loading times have increased, that indicates a regression.

Another key aspect of regression testing is how it can work together with other testing schemes to produce synergistic effects. Here are a few:

• Exploratory testing: Exploratory testing can be combined with regression testing to yield more results for analysis. The two operate differently: regression testing sets out to confirm expected system behavior after using scripted tests, while exploratory testing locates unexpected issues through unscripted developer exploration. Nonetheless, the two testing schemes can be used in a complementary way so that each informs the other. Some organizations use an outright combination of the two—exploratory regression testing—that gives developers direction yet flexibility. For its part, exploratory testing can help improve existing cases or new test cases and encourage more comprehensive test coverage.

• Continuous testing: Similarly, regression testing is often used together with continuous testing. As its name suggests, continuous testing involves constant testing practices being integrated into the complete SDLC. Constant or continuous testing is an established part of regression testing. Regression testing couldn’t really operate as intended without continuous testing. Continuous regression training—a mix of the two—gives testers more of a free hand when zeroing in on high-priority test environments that might have bugs or other issues.

• End-to-end testing: Another technology used with regression testing is end-to-end (E2E) testing, which implements realistic user scenarios to validate the entire workflow of a system, from end to end. E2E concentrates on user experience as well as components like the interface, backend and related databases. Regression testing and E2E are complementary pursuits to the extent that regression testing can even include total E2E tests within it, and E2E testing can indicate the presence of issues requiring remediation through regression testing.

The wide-ranging effects of AI are astounding. Few industries are so heavily invested in AI as the technology sector, and regression testing is one of many technological processes that is being radically accelerated by the power of AI.

The phrase “accelerated” is apt because the main way that AI is enhancing regression testing is by maximizing the speeds at which its various conclusions are reached. However, AI is also increasing the accuracy of that test data.

Specifically, AI is using its algorithms to build relevant test cases by analyzing historical test data, user behavior and code changes. This helps in prioritizing tests according to predicted impacts. And when AI runs those tests, they are run faster and produce quicker test results.

AI even enhances the nature and quality of regression tests by using defect detection methods and self-healing tests. This can keep automated tests working well, even in situations where development continues. Ultimately, AI improves regression testing by enhancing decision-making and automating tasks, which reduces costs and speeds up time to market.