Software testers are welcome into the new world where AI-driven tools are the new norm. Testers are stressed out about their jobs and wonder if artificial intelligence (AI) is going to replace them. However, this transition from traditional testing to AI-powered testing is an opportunity for testers if they remain on the right track. It is easier for software testers to make their jobs interesting and profitable. So where does a software testing company see itself in the wake of the current scenario?
Test Engineers Converting Into ML Engineers
Let’s consider the most highly paid jobs at Google, they include employees working on search and AI. well, if you are wondering what these professionals actually do, the answer is that they work on web search and are known as search quality engineers. These engineers come up with new test cases that are extracted from the test results of the last version of the search engine. Although this seems like a tiring task, yet they look through all test data for issues or defects that need to be fixed. Once all the defects are identified, they work on resolving the problems. In order to resolve the issues and simplify the process, they emphasize factors like a search term that shows up in a document with a similar frequency. Testers change only value or two in the configuration file. They test, and re-run multiple search queries through this new version of the search engine and again skim through the data to see if the results have improved or not. What is worth the attention here, is that they are not writing code. This involves rigorous testing, just a bigger scale especially where the results are more quantified.
Testing and More Testing
Ever wondered, what those AI researchers at Google do all day long? Typically, the answer would be they test all day long. While the basics of machine learning (ML) include a lot of test input examples and they know their respective outputs. These ML engineers try different algorithms for the simple testing process. They spend most of their time testing these software testing tools and algorithms. As mentioned earlier, test engineers do not write a lot of code, but when they do it, they often write additional testing code and a software testing company pays them really high as they are termed as ‘sophisticated’ testers.
Conclusion
These Search and AI engineers are equipped with visual tools to connect data pipelines and mark parts of the application that require changes and can be improved with ML tools. They also need AI and ML to keep up with the ever-evolving world. Due to their hard training, and rigorous testing, testers do not need a lot of skills to become a machine learning engineer. They also have query and visualization tools, that allow them to keep track of how AI is assisting them in improving their software testing process. A software testing company encourages its software testing teams to explore all possibilities with AI and ML-powered testing tools and solutions.
