Testing is about finding bugs, but it’s also about identifying potential issues and regressions that might be overlooked by the tester and user alike during normal use of the application/system being tested (ease of use).
If a problem occurs, it should be reported as soon as possible (even if it’s “unexpected” when the test was initially created to be fixed before any further damage is done. This article will elaborate on the factors one should consider while performing regression testing.
What do you mean by Regression Testing?
Regression Testing (also known as Software Verification) is used to test whether the current version of an application works correctly or not after modifications have been made to it. Regression testing also includes tests of the original version of the application against a baseline test suite.
This can often be done automatically using Test Automation tools. This process takes time but is essential for a robust software development project. It should start at the planning stage of any new software development or re-write existing systems that have been released and are now under maintenance or support activities with customers.
You can use various techniques to test for regressions, including comparing two versions or running the same tests on two separate branches (a baseline test). There are many reasons why organizations undertake regression testing of the product and improvement project.
However, when considering this activity, the exercise should always be stated upfront. For example, one may ask, Which factors should we consider during regression testing?; factors such as Time Window, Pre-requisites, Environment, Data, Landscape scope, Prioritisation of risk, Automation, Script maintenance, Full UI regression, and Output Analysis.
What is the meaning of successful regression testing?
An essential part of guaranteeing software quality is regression testing. If executed successfully, the provided software will be more resilient and reliable, and its quality will continue to improve with each release.
Applying all the essential factors explained in the article will guarantee that every release of your product is as bug-free as possible.
Vital Factors to Consider During Regression Testing
- Time Window
The regression test ensures your app works well enough for users before hitting the App Store or Google Play Store. While there is a period for the app to be on the app store, it will cost the developers and company in the long run. The time window is vital for regression testing and concluding the viability of the app. Each has its own set of considerations that must be considered.
Prerequisites are another vital factor to consider during regression testing, and it is solely considered by the people who perform the test. The whole point of considering this factor is so that we don’t have to guess what works and doesn’t. So it’s best to make sure everything is in place before running an entire test series instead of running after building your software. Prerequisite primarily considers finding out that a problem with some piece of hardware or software on a particular day caused a failure in the test run, and you missed it by seconds and hours.
Without considering the environment and reliability, the regression test can’t be undertaken. It’s a good idea to set up a build (test) that is not connected to the production environment live site and use it for these tests, as you can be sure that your code will work correctly before the customer sees it. This is where the smoke testing is vital. To ensure your application performs as expected, it is essential that you have a robust smoke test running before each release or when any changes are made to your application codebase; these are known as unit tests, integration tests, or functional tests (depending on the scope of testing).
Test data is the prior requirement before performing a regression test. Standard data can also be utilized to find out the older defects in regression testing. While working on the test plans and test procedures, the data from these systems can then be used for regression testing and code reviews (which I think is the most useful way of doing it).
- Landscape Scope
At some point of time during the test, there can be necessary use of Stubs or API calls to perform or mimic specific software and applications. This mimicking is necessary to grasp the responses of particular applications in case they are unavailable at the time of performing the test. It allows you to visually see where each condition fits within your project in terms of scope, priority, risk, etc., and what testing steps have already been completed on that requirement so that any future testing steps can be determined based on the current status of the project at hand.
- Prioritization of Risk
After the successful execution of the Smoke test, the developer or tester must consider the sanity test. It will help them verify all the vital processes for the presence of any bugs or malware that can cause harm after the app’s release. If this is an internal application, will there be any negative impact on other parts of the business? Prioritization can be the factor that is essential for concluding all the responsible impositions before the introduction of the app. Therefore, it is essential to keep track of what has already been tested or proven, as well as what needs to be tested next.
The following areas which must be considered to be inspected are:
- Most used processes.
- Areas with recent changes.
- Recent defects fixed.
- A clean run and negative testing.
- Historical regions of defect density.
It has an automation strategy that promises you on-timely test completion and value-for-money for your investment, rather than just keeping the tests running forever and not knowing what to do with them. When they reach their end of life or are no longer relevant to your business needs and requirements, it potentially causes a lot of manual testing, time wastage as your testers try to fix issues where none exist.
- Script Maintenance
Script Maintenance is another factor to consider during regression testing. Suppose the automation can get manipulated even in the absence of impediments. Automation allows you to quickly identify any regressions and take remedial action without re-running the tests on every change to your codebase or manually testing every possible scenario yourself. But somehow, Automation can only make things easier for us but sometimes may fail to perform as per the mechanism. This is where script maintenance is necessary to cope with such a scenario.
- Full UI Regression
The only good place to start is to test that the UI will render correctly on screen with a different resolution, font size, and DPI settings (to simulate real-world conditions). Once you have done this, you can move on to testing the various scenarios like testing the user interface when the application starts up – how do things look when it first starts? Does the correct information appear in the right places, if not, what happens? Are there any unexpected results? Is the data showing up? What about custom fonts or images, etc.
- Output Analysis
Most of the time, Automation can take hours to execute the task. If you run the automation at night, the results can only be reviewed the next day. In such a case, a primary high-level pass/fail must be considered in the analysis. After that, look out for the exact location of the error and resolve it with appropriate steps.
The Bottom Line
Planning and Execution are a vital part of the regression test, which are most often conducted by developers during the early phases of a project. This is a stage when there is little or no information about the requirements of the product being developed. This is where TestGrid plays an efficient role with its team of specialized developers who have been proficient in running regression testing on a number of practical use cases. The TestGrid team tests the entire system through multiple iterations before any code is written. The final stage would be regression testing with the system under load to see how it responds to the expected workloads.