Future of Software Testing: Artificial Intelligence Assistance

About the presentation

Nowadays, researches are looking for adaptation of Machine Learning algorithms to testing processes to reduce the manual effort and improve quality. In this talk, we will discuss in detail Machine Learning practices with a case study.

We start with a quick view of the machine learning types. Then, we list AI applications in testing these perspectives: test definition, implementation, execution, maintenance and gmx jrouping, and bug handling. What’s more, we do not only present existing AI applications but also what can be done in the future. Finally, we summarize the application areas with algorithms and discuss the advantages and potential risks of AI applications in software testing.

To sum up, we target at an important problem, AI-based applications of software testing. As more and more researchers try to use AI techniques to solve the traditional software problems, “what and how we can use” becomes more crucial. AI is one of the hottest topics in software world nowadays. Especially mining valuable information from bugs can be made use of by managers to guide feature priorities. We make the outline well organized and easy-to-follow. We introduce the applications in different stages of testing, that makes audience easy to find what they want

Who will benefit

Test Automation Engineers, Test Architects, Test Managers, Developers.