A study has been done with over 1,600 software testers, and it has found that 78% of them have used AI to help improve their productivity. The LambdaTest report shows that companies are working hard to provide greater software reliability, using AI as a means to do so. The report indicates that 51% of testers use AI to automate the creation of test data, and 45% use it for writing code for automated tests. 89% of organizations are also automating the running of tests through CI/CD tools.
How AI Could Be Utilized in Software Testing
When AI finishes a task supplied by a person, it then learns from it. Over time, AI can improve its learning capabilities, performing the task more efficiently each time. AI eliminates a lot of manual testing efforts, meaning that software developers can speed up their time to market while improving resource allocation.
If you look at the online casino market, you’ll soon see that this is heavily reliant on software. Although you can try to determine the best numbers to bet on roulette, AI guarantees a random outcome every time, ensuring that it remains a game of luck. As AI, in the form of a RNG is used to determine each result, developers can significantly speed up game creation.
Casino software developers can release many games a year, not only using AI to determine random outcomes but also using it to calculate the exact RTP rate, ensuring each game falls within the appropriate margins. This is a prime example of how AI isn’t just used to create software, but it’s also being used to test it for fairness, along with bugs and glitches. With AI testing, swift feedback can be given across multiple devices and environments, with consistency and repeatability.
AI Could Improve the Quality of Software
A software can recognise what test cases have to be run while automating them for execution. When AI software knows what areas have been changed in the software code, a risk analysis can then be done to ensure what test cases have to be executed. This ensures that nothing is broken before the software’s release. Test planning is also a huge part of AI testing.
Planning what test cases should be created when new features are released, while automating workflows is huge for software developers. When the taster automates a single workflow, AI software can then automate similar ones, saving a great deal of time. This helps to free up the developer’s time, allowing them to work on more innovative advancements, while giving them more room for creativity and dynamic working opportunities.
With AI becoming integral to our lives, it’s not surprising to see that it’s becoming a huge part of the software industry. With software testing being so time-consuming as it is, AI is a great solution for not only speeding up how long it takes software to hit the market but also ensuring that when it is released, bugs and glitches are kept to a minimum.