Quality assurance teams use regression testing to analyze software performance after each code release, protecting existing functionality by revealing unintended changes to the overall application.
Most regression testing processes include five essential steps - detecting code changes, prioritizing changes, assessing entry point and entry criteria, identifying the exit point, and scheduling the regression tests.
Quality assurance teams often create massive regression test suites to ensure coverage, but this can cause delays and bottlenecks in the software delivery process. Launchable solves this velocity hinderance by helping you automate regression test selection.
Modern software is built over time with a patchwork of code releases to introduce new features, update existing features, or fix bugs. And each new code change has the potential to adversely affect other parts of the software once released.
Quality assurance teams use regression testing to analyze software performance after each code release. This protects existing functionality by revealing unintended changes to the overall application, which ultimately gives development teams more confidence when delivering new software releases.
In this post, we’ll cover all the most frequently asked questions so that you can expand your knowledge beyond the basics of regression testing.
Regression testing is a form of software testing that helps quality assurance teams verify that changes made to a codebase do not affect the application’s intended functionality. This involves re-running test cases against a new version of the software to ensure they still pass. Regression testing also ensures bugs are actually fixed and don’t reappear later on.
Software tests are often performed on a code change itself, but there’s always a risk that the new code impacts the overall application in an unexpected way. That’s why analyzing the application performance after a code change through regression testing is crucial for improving overall software quality.
While regression testing may sound similar to retesting, it serves a very different purpose. Retesting is aimed at digging deeper into a specific problem to determine what is wrong or confirm that a particular bug is fixed. Regression testing is performed on a regular basis as part of a code release process.
There are a number of situations where regression testing should be applied:
A new feature gets implemented
There are new requirements for an existing feature
A bug or defect gets fixed
The software configuration changes
The codebase is refactored to improve performance or readability
Related Article: Seven Types of Regression Testing
The term regression testing comes from regress, which means to return to a former state. The aim is to ensure the new software version — with the exception of the new code changes — matches the functionality of the previous version. This requires analyzing the new codebase against the former state of the software’s performance.
Detecting code changes to understand the potential impact on the overall software
Prioritizing changes to identify the most critical regression test cases
Assessing entry point and entry criteria for the new codebase
Identifying the exit point for the mandatory minimum conditions
Scheduling the regression tests for execution
While many organizations implement these steps using automated regression testing, there are ways to perform regression testing more optimally. For example, one of the greatest bottlenecks to regression testing — and software testing in general — is attempting to run a large number of test cases too frequently. By strategically prioritizing test cases, teams can speed up regression testing and improve software quality much more efficiently.
Most companies use an automated regression testing tool to create and run test suites, and ideally choose a solution that can integrate with their unique software development lifecycle (SDLC). There are open source options, such as Selenium or Serenity, which provide basic test automation capabilities. Automated testing tools like these have enabled repeatable and scalable testing, but many of them still have a negative impact on development velocity.
The next evolution of software testing tools are more comprehensive platforms like Launchable that can offer a reliable and efficient experience for development teams. With previous automated testing tools, many quality assurance teams still manually select test cases in an attempt to overcome software delivery bottlenecks. A modern software testing platform can use intelligent test prioritization to speed up test runs, and in turn, development velocity.
No matter how small a code change might seem, it still has the potential to impact overall software performance in unexpected ways. Regression testing is a way to mitigate this risk so that development teams can launch new releases with confidence.
Regression testing goes beyond functional testing by assessing the broader impact of code changes. While functional tests ensure new features work, they’re usually new test cases limited to the code changes themselves and don’t evaluate compatibility with existing features. This is crucial because releasing new features that improve the software product as a whole rather than breaking it is a surefire way to improve the user experience over the long term.
Without using regression testing, every new code release could have a negative impact on software quality that wouldn’t be detected from functional testing or other types of software testing. That means implementing regression testing is a way to lower the risk of new releases. By performing regression testing early on in the development process, it also greatly reduces the cost of a potential defect.
The major challenges of regression testing include: changing requirements, complex test cases, and large test suites. Since regression testing is aimed at reducing the risk of each new code change, more frequent releases also require more frequent testing. That means quality assurance teams will usually need to prioritize certain test cases to keep pace with development velocity.
In addition, applications can grow very large and complex over time. This makes it much more difficult to implement adequate regression testing. Quality assurance teams will create very large test suites to ensure coverage, but this can cause delays and bottlenecks in the software delivery process. Once again, this highlights the importance of strategically running fewer test cases to balance development velocity and software quality.
Launchable is a developer-first software testing platform that can help you automate regression test selection. Using machine learning, Launchable can predict the test cases that have the highest probability of failing based on your code and test metadata. This helps your development team focus on what matters most, leading to faster and more reliable software releases.