Use Input Data, Output Data, and Analytics to Drive Your Testing
We keep hearing about the Internet of Things, big data, the explosion of analytics, and all the other factors driving innovation in software development and testing. It’s exciting, for sure, and just the thought of smart cities and regular devices making use of the Internet in creative ways can make your head spin.
But none of it means anything if you can’t find a practical use that allows you to better test your software. Why care about all the data you’re collecting if you don’t have smart ways to leverage it? Why rave about analytics if your team continues doing things the way they’ve always done them before?
Geoff Meyer, a test architect in the Dell EMC infrastructure solutions group, spoke at last year’s STARWEST conference about data and its impact on software testing. He put in plain terms how the data you already have can be used to your advantage.
“If your organization already has structured data, which they probably do in the form of defects...Logging defects, logging test cases, keeping test configurations, generating defects. Storing that back in there, you've got a really good set of data, of input data there,” Meyer said. “And then you also capture your output data, your test results, whether it's logs or whether it's test case failures. That's all stuff that then can be fed back into an analytics engine to start optimizing and looking for opportunities for you to identify, for us, it was trying to identify our high-value configurations. Our test configurations.”
By looking at all this data—your inputs, outputs, and configurations—you can better understand where you have bottlenecks. You can discover the roadblocks that might be slowing your entire software lifecycle down, and it might just take a few smart tweaks to optimize your team.
The industry keeps growing in complexity, and because of that, there are more things than ever that need to be tested. And beyond that, quality expectations by your users are as high as they’ve ever been. You can’t throw a less-than-complete project out there without backlash—and users likely dropping your app before you have time to fix it.
By studying the data you have and making use of modern analytics, you can allow your team to run more smoothly, complete certain tasks with fewer resources, and give yourself a clearer lane to better software.