Developers would admit that the complexity of the code increases multi-fold with the progress in product development. Scalability comes with its own set of challenges – one of them is ensuring that the new code changes have no side effects on the working functionalities.
Changes in the code can spring up some surprises for the development and QA teams! This is why continuous testing becomes inevitable as it helps in keeping up pace with the existing software changes. Continuous testing, CI/CD, and DevOps have become an inseparable part of the software development and testing process.
However, having all different varieties of tests (e.g. UI, smoke, performance, integration, regression, E2E, etc.) as a part of the CI/CD pipeline can elongate the delivery timeline. Though the choice purely depends on the type, scale, and complexity of the project; it is essential to have regression tests in your CI/CD strategy.
For starters, regression testing is a form of testing that helps in ensuring that the newer code changes (i.e. fixes or feature enhancements) have zero side-effects on the existing code. Having automated regression tests as a part of the CI pipeline plays a huge role in reducing the developer feedback time and improving the product quality at a rapid pace.
Like any other form of testing, regression tests cannot be fully automated! Since automation can reap a lot of benefits, it is recommended to automate the majority of the regression tests since automation and CI/CD go hand-in-hand. In this blog, we look into the nuances of running regression tests in a CI/CD pipeline. So, let’s get started…
You would have come across umpteen scenarios where new feature implementation or bug fixes lead to other bugs. Buggy patches, untested code, undocumented information, and many such reasons can hamper the existing functionalities in the product.
To avoid this leakage, it is recommended to run regression tests for bug fixes (or implementation) that can have a wider impact on the other features in the product. Irrespective of whether you are using monolith or microservices architecture, automated regression tests can reap significant benefits.
Automating regression on REST APIs must be considered for any type of architecture (monolith or microservices). It not only helps in unearthing bugs but also helps in increasing the test coverage. All these factors eventually help in improving the product quality!
Here are some of the major types of regression testing:
Apart from the above categories, you also have the option to perform complete and partial regression tests. As mentioned earlier, the type of regression tests purely depends on the gravity of the fix (or implementation). In case there is a change in the code that does not have any external impact, you can opt for selective and/or unit regression tests.
This decision is super important since tests regression run in the CI pipeline takes time to execute and you do not want to run unnecessary tests since they would stretch the release cycles.
Also Read: Difference Between Regression Testing and ReTesting
In the earlier section, we had a look at the basics of regression tests along with deep diving into the major types of regression tests. The test duration and test infrastructure has a direct correlation with the developer feedback time. Hence, it is essential to seek support from regression testing services companies to make the best out of this test type.
The integral question is “What types of regression test(s) should be a part of the test plan?”. Here are some pointers that might be helpful in arriving at that important decision:
As the name indicates, complete regression tests comprises tests that help in verifying every aspect of the AUT (Application Under Test). Though the execution time of these tests largely depend on the test design, infrastructure, and other such factors; the time duration is said to be higher than other forms of regression tests.
Taking the above factors into consideration, complete regression tests must be run in a CI/CD pipeline only when there are massive architectural and code changes in the AUT. With complete regression tests, you can achieve close to 100 percent test coverage.
This form of regression test involves adding more test scenarios and/or enhancing existing tests in the test suite. Ideally, partial regression tests must be preferred over complete regression tests if there are no major changes in the AUT.
Since you won’t be running all the tests, it is important to choose the best-suited tests for partial regression testing. An automated test impact analysis must be done after the code changes are approved, whereby you would have a better idea about the gravity of those changes.
Based on the results, you can choose the tests (or test suites) that should be a part of the partial regression testing plan.
Also Read: How To Optimize Regression Test Suite?
There is a thin line of difference between partial regression tests and selective regression tests. In selective regression testing, tests involving a particular service (or component) are chosen if changes are made in the underlying implementation of the same.
In ideal cases, selective regression tests are best-suited when you have to verify the functionalities of a particular unit/module. Hence, it is also called unit regression testing.
This form of regression testing is ideal when there are minimal (or no) changes in the existing codebase. This also means that there would be ideally no changes in the product functionalities.
So, why choose corrective regression testing? Well, the simple answer is to unearth issues that might have gone unnoticed in the earlier regression test cycles.
Also Read: Why Regression Software Testing Is Critical In Fintech?
Like any other form of testing, automated tests in the regression phase will reap benefits like faster developer feedback, improved product quality, and much more. You can use automation frameworks (or tools) like Selenium, Cypress, Robot, etc. to create automated regression tests.
You can also use tools like Postman to create regression tests for ensuring that the APIs do not break in the production. Automated regression tests can be conducted across different environments – staging, pre-production, and production. Data-driven regression tests must be considered for tests subjected to a large amount of data.
Once the regression tests are ready, the next step is to automatically trigger the respective test suite whenever there is any change in code. This is the test execution stage where CI tools like Jenkins, Circle CI, etc. are leveraged for running tests in a continuous manner.
In most cases, code changes in the development phase will also involve changes in the regression test suite. This additional overhead can be reduced by auto-healing of the test suite by using the best-suited automated AI testing tools. This factor also improves the product quality and accelerates the product delivery.
Also Read: Top 10 Regression Testing Tools
Choosing the ideal CI/CD tool is important for maximizing the benefits offered by regression tests with CI/CD. This is where the expertise of an experienced regression testing company can be useful in short-term as well as long-term!
Apart from this, regression test suites must be robust and maintainable so that tests can be added at a quicker pace. All of this helps in improving quality, shortening the developer feedback time, and expediting the delivery of the product.
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