The Ultimate DevOps Playbook
All software needs to be tested before it can be released. And when release cycles are accelerated, this can place enormous pressure on QA teams. This is especially true given the proliferation of ways in which end users interact with software.
For example, a service may be available as a website or an app. Both will have to work on multiple platforms on thousands of different devices. They may also have to interact with other websites, apps, or services, such as payment gateways, geolocation services, or review services. The need for software to be tested with more permutations more frequently means the number of possible test cases increases exponentially.
Similarly, as we add more features, we need to add more test cases and also maintain an ever-increasing set of tests as the product line matures, and the load on the QA team increases significantly.
Automation is therefore key, with testing of functional and non-functional requirements built into the development and release process. The trouble is that this doesn’t always allow for comprehensive testing. Exploratory testing can be a challenge, for example. Exploratory testing involves using the software in ways that weren’t necessarily anticipated by developers. Deviating from the script in this way can be a useful route to uncovering bugs, as well as being more representative of real user behavior, which frequently fails to conform to what the developers originally had in mind.
It is becoming less and less possible to make assumptions about the way people will use your software. This means you need AI and predictive analytics to help you understand how people are using your software and feed that insight into the development and testing process, so you can focus on and optimise business performance.
Download this playbook to understand how AI has a key role to play in analysing and drawing insight from the vast amounts of data in our increasingly complex, interconnected, software-dependent world.
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