Let’s continue the from the last post where you saw a working implementation of a learning environment called Pacumen. Here I want to provide you more details of the basis for this kind of work and use that as a springboard for thinking about how testers fit in these situations.
Category: AI
Pacumen – Exploring Testing and AI
In this post I want to set the stage for some future posts regarding thinking about how you might work, as a specialist tester, within the context of an environment that is using machine learning and various artificial intelligence techniques. This is an area that I’m finding many testers are not ready for. To that end, I’m going to show you how to get my Pacumen code repository up and working. Then I’ll take you through a few exercises to put it through its paces.
Testing and AI
What’s been interesting in the testing world — at least the part of it that I hang out in — is the application of different AI-based learning algorithms to the act of exploring an application and seeing what (if anything) that tells us regarding the algorithmic and non-algorithmic parts of the testing discipline. Let’s talk about this because I think is fertile ground for testers to be exploring.