Application of AI in testing

  from 20 century 50 From the early s to today's Advanced Robotics , Algorithm driven machine learning , Artificial intelligence has come a long way in a very short time . Although AI is still relatively young , but QASource Finding the current and potential value of artificial intelligence for automated testing is huge . As applications become more complex , The rapid development of software development life cycle and cross industry high-speed competition time to market , The engineer will get all the help available , Whether it's from machines or others .

that , Why? AI Good for automated testing services ？ In short , It allows machines to learn and understand the environment , perform “ intelligence ” operation , And automatically improve themselves .

Let's see how these three features can improve your automated test plan in the near future - And how it will save you a lot of time , Money and resources .

Failure prediction

QA The engineer's greatest asset is him / Her experience . According to their field , Experienced test experts are familiar with common errors . They can even predict the location in the application .

Now? , Imagine using the combined knowledge of such a team of engineers to program AI robot . some time ,AI The robot will use predictive learning to detect stop displayed errors early in the development life cycle .

Minimize detailed testing

Although automated testing has changed the rules of the game , But in AI With the help of, it can finish . Even if there is a good automation program , Engineers still have to manually test edge conditions and other complex configurations .AI Robots will soon be responsible for driving these types of tests , And repetitive manual tasks , For example, click the button in the interface , Enter valid and invalid data into text fields, etc .

Driving performance test

Imagine , Test every operation in the application , Capture all regression defects after each build , And see a clear analysis of the slowest part of the application in a few minutes . AI driven performance testing will help generate clearer data faster than current automated processes , A more cohesive report , This makes your team more agile and responsive to key performance issues .

Improve coverage and quality

Automation has achieved unprecedented application coverage and test quality , Therefore, the power of artificial intelligence is unimaginable .AI The robot will be able to test each scenario in the test case using a variety of data combinations . Because of machine learning , Robots can discover new behaviors while running , And use it in the scene . This kind of power , Fast , In depth testing will help to improve product quality - Exponential growth .

Faster time to go online

AI The robot will be able to analyze and learn your entire application in hours , Not the weeks and months of a human Engineer . This will lead to rapid drafting of test cases , Faster execution .QASource Created a AI engine , Not only helps reduce false positives , It's also shortened QA Agreed regression analysis time 60％. In addition to reducing the amount of work required by engineers , take AI Combined with automation means that you will be able to deliver new versions to customers faster than ever before .

Economic solutions

People are QA An important part of the team , It's always . But for some jobs , It's easier to rent a machine , More efficient , Cheaper . Writing and maintaining test code is one of the tasks , Fortunately, , For all of us ,AI Robots are good at . Automation driven by artificial intelligence will be a one-time investment , Will bring a huge return on investment .