In 21st century AI is coming to change our vision for life. It is everywhere in our daily life: may it be while commuting, working or just relaxing.
We are unconsciously in touch with AI and it will become more and more integrated into our daily lives. Nowadays many professions are trying to implement AI in their working process. And now we are going to see how AI is helping to do Software Testing.
Wikipedia defines AI research as “…the study of “intelligent agents”: any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.” In other words, it’s the ability of a computer program or machine to think and to learn.
How AI is changing Business models
As the software economy grows, enterprises push towards digital transformation and consumers have become more demanding and impatient, software development and testing can’t be in a match using traditional methods and practices. Businesses now demand real-time risk assessment all over the different stages of the software delivery cycle.
Speed – is all that matters in product delivery and one of the best and most efficient ways to achieve it is to implement machine learning and AI in software testing practices.
So the use of AI in software testing could arise as a response to these changing times and environments. AI could be of great help in developing failsafe applications and to enable greater automation in testing to meet these expanded expectations from testing.
For example, consider that most (if not all) test automation tools run tests for you and deliver results. Most don’t know which tests to run, so they run all of them or some predetermined set. So what if an AI-enabled bot can review the current state of test status, recent code changes, code coverage, and other metrics, decide which tests to run, and then run them?
So what comes next? We are in an active R&D era, trying to continuously implement applications of artificial intelligence and machine learning to augment our software testing tool kit. There are many means of research, but the end goal is clear: to support teams develop and test their code more efficiently and effectively, to create higher quality software at speed.
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