"Our test suite passed," the developer announced. The business analyst looked at the console output - pages of cryptic assertions, stack traces, and technical jargon. "Great," she replied. "But what did it actually test?" The developer scrolled through the logs, searching for something human-readable. Nothing.
The thesis that "manual testing will be a cheaper and more effective method than automation" continues to appear in testing discussions, webinars, and publications. This perspective represents a widespread but oversimplified view of software quality economics. While manual testing offers lower hourly rates and immediate deployment, this perspective fails to account for the complexities of scale, the many scenarios where automation isn't merely preferable but essential, and most importantly the evolution of testing technologies.
We've all seen it happen. The developers on the team excitedly discuss the latest framework they're implementing, while the test automation engineers quietly stick to the same Selenium scripts they've been maintaining for years. It's a strange disconnect – the very people who should be at the forefront of technological validation often trail behind when it comes to evolving their own toolset.
CenterTest provides numerous means for effortless Guidewire application testing, such as simplified test creation, requiring only basic Java knowledge.
A transition from manual testing to automated testing is a project on its own. Hiring resources with new skillsets, introducing or developing new tools, requests for additional infrastructure and environments, is a guarantee. All this translates to a bigger upfront investment in comparison to manual testing. Without fixed expenses nor clear predictable gains at the start of a transition, calculating the ROI of such endeavor is not a simple task. Here we will point to several less obvious aspects which need to be taken into consideration when estimating the ROI. What to balance all the costs with?
Every test automation needs investment to start with. With every new test, the overall execution time increases. Why write so many new tests if you do not have time to run them? What is the point of using Data-Driven Testing to multiply those numbers even more if you are already out of time? The most common solution is to add more manual testers, however, this means an increase in cost for testing. Is there a way to avoid that?
Guidewire test automation,
