We live in an era where software development has been revolutionized by AI (Artificial Intelligence) & ML (Machine Learning). It is expected that testing will be taken over by automation with its new developments and advancements, but that is not the case. Software manual testing has been around for many decades since initial software development, and the industry has taken multiple shifts. However, its scope remains the same. In this article let us explore the impact automation testing has over manual testing.
Why is manual testing still relevant?
New Projects: Projects in pilot phases which begin as a concept and take shape during early sprints require testing to be done manually. Using automation testing during the initial phases of a project would be expensive as it undergoes continuous changes. Using manual testing in these cases would be cost-efficient and easy to accommodate changes.
End 2 End Testing: Automation testing can be used to test single systems or integration levels in detail. Whereas, End 2 End testing involves multiple systems and require manual testing. Automation testing that runs an End 2 End test scenario has many challenges, especially systems have different tech stacks. Design changes involving systems in End 2 End testing impacts maintenance cost.
Maintenance Cost: For small projects or components, automation testing costs higher than manual testing. Performing quick manual testing would suffice for smaller projects/ components that undergo frequent changes rather than updating test scripts after rerunning those tests manually.
UX Testing: Maintenance costs are proportional to UX changes. Each time UI/UX change, test cases break and raise a false fail. When changes are encountered in a script, there are rework/ maintenance to achieve the test pass. This impacts the next UI changes again. So, for an application with frequent UI/UX changes, automation testing is costlier than manual testing.
Visual Testing: While there are few automation tools available in the market, AI & ML are incorporated with visual testing to achieve 100% test result. But the number of hours required to train AI to understand minute changes in UI would be expensive than performing manual tests. Sometimes, human eyes can find a little misaligned text boxes, which could be challenging for an automation tool. Such automation tools with AI & ML are expensive compared to manual testing.
User Acceptance Testing: There is no way user acceptance testing could be automated. Beta users/client team must experience the end product by simulating user experience using manual testing.
How automation testing can be leveraged?
Let us discuss the areas where automation has to be implemented to support manual testing efforts.
Regression: When a part of the product is regression and the product or UI changes, tests have to be automated using open source software. Using automation testing can therefore save manual testing time.
Integration Testing: API level automation can be quickly created like manual testing. Tools like Postman enables to create tests that can be automated using runner feature. When manual testing is performed, requests are stored as collection. This stored collection can be run any time as a test suite to rerun the test scenarios.
Smoke Test on CI/CD: Automating test scripts for smaller projects are expensive. However, using smoke test scenario would reduce the cost. Smoke tests undergo changes to get added to CI/CD pipeline for project code deployment capturing blocker/showstopper issues during code deploy to QA/Stg environment, before the code is released to production.
Manual and automation testing complement each other. Manual testing is as important as automation testing and there can be no project that is purely manual. There will always be an area where automation can be leveraged with open source tools which are no-cost and low maintenance. No project can completely use automation testing as client expectation keeps changing; manual testing is the way to handle frequent changes and ad-hoc testing requests. It is up to the project management to decide how and where manual and automation testing have to be implemented to provide a customer satisfied product delivery.