It is the hard truth that testers and developers spend too much of their work-life waiting. There is still inefficiency in software delivery. This can be solved by the use of AI. AI works best when it has many data to analyze and find the trends, risk, prediction, and solution to the problems. Today’s complex application it is hard for humans to analyze data and make a split-second decision on where to focus test. Therefore AI is becoming a game-changer for testing.
AI can reduce quality risk, even though there are many test stages before the product delivery the delivery team may have only few knowledge in code, how code is executed, this lack of understanding lead to quality risk, this causes the escape of defects and it may cause in the quality of the product. So if we have much data for the AI about the quality of coding then these kinds of problems can we solved and a much high-quality product can be delivered to the customer.
AI also reduces the time taken for testing. When we do regression it is time consuming if there is AI it can understand what kind of test should we do and AI can also identify which code has changed automatically produce test suit based on the application risk. This helps in selective testing, and to understand which part of the application is frequently used and risky. This also helps to understand the trend of which test has the right number of failure so that the company can study this and take the necessary precautions in future projects. This will help to find defects faster and can be reported to the developers quick, this helps in the faster product delivery and also helps the tester to have a gratification if defects are found.
Today world of software applications and microservices are incredibly complex to the faster delivery and the short life cycle is in demand, so the introduction of AI will help to maintain the velocity.
Trainee Infaum Edutech