Role of AI Testing in an Agile Environment
We will discuss how AI (Machine Learning, Natural Language Processing and Artificial Intelligence) is affecting the world of Software Development and Testing. We will look at different tools that provide AI Testing - and what are the key challenges they solve as part of their solutions.
AI Testing is a vast field - and different solutions target different types of testing use-cases. Whether we want to develop self-healing test-cases that always stay up-to-date for a given product, OR come up with a generic test-suite that can work across a tier of web and mobile applications, AI Testing offers solutions that can be robust, scalable and work in conjunction with in-house testing paradigms.
I intend this to be an open discussion forum providing insights about the different AI tools that we have found helpful and others that are not-so-helpful.
Outline/Structure of the Talk
Following is high level outline of the presentation:
- What is AI testing and why should I care?
- What types of problems can be solved by a AI Testing Approach?
- What are the currently available AI Testing tools and what functionalities they provide?
- Open source AI testing alternatives
- How AI Testing can fit into my organizational needs?
- Good and bad about these AI Testing tools.
- Q&A and Discussion.
At the end of this presentation, I hope to have informed the attendees AI Testing Paradigms, different tools and frameworks and how they can utilize these tools within their organization.
Instead of pushing a generic one-size-fit-all solution solution, we are going to break down parts of AI Testing that can be useful for attendee's specific needs and use-cases.
QA Managers, QA Practitioners, Product Owners, Team Leaders, Managers, Directors.