This post continues on directly from the first one in the series. We’ll take the CartPole example we started with and continue our journey into how testing — particularly that done by a specialist tester — intersects with the domains … Continue reading
Author Archives: Jeff Nyman
As a tester are you ready to work in environments that are based in or around data science and machine learning? What will you actually do in these environments? How will you interact with developers? How technical do you have … Continue reading
In a series of posts, I’ve talked about my Tapestry micro-framework and I tried to provide some of the rationale for its design choices. Providing that rationale meant providing a context for you to see it in action. This post … Continue reading
In the previous post I talked about communication patterns in terms of the micro-framework and tests. Here I’ll talk about the expressiveness of the tests themselves, showing how Tapestry supports the idea of a context.
In my last post on micro-frameworks, I got into the organizing principles of my Tapestry solution, by which the framework provides or supports a mechanism for the encapslation of and delegation to logic. Here I’m going to continue on that … Continue reading
This is a continuation of my exploration into providing insight into micro-framework creation for automation, using my own Tapestry tool by way of example. The first post set the context and the second post focused on exposing an API. Here … Continue reading
Here I’ll continue on with the introduction of my Tapestry micro-framework that I started in the first post. This time I’ll focus on a bit on how you want to create an API interface for your micro-framework.
Here I want to talk a little about test automation framework construction. Or, rather, micro-framework construction. I will use my own tool, called Tapestry, for this purpose. Tapestry is written in Ruby but what I talk about is potentially transferrable … Continue reading
This post continues on from the first part where I went over the high-level details of a tester getting involved in a machine learning context. I left off just at the point of introducing the algorithm and letting us get … Continue reading
I’ve talked before about the intersection of testing and AI as well as provided a series of posts, using a Pac-Man clone to further introduce testers into algorithmic searching. Here I’ll consider a really simple example of engaging with a … Continue reading
Earlier I talked about describing my own role. I think what I said there is almost interesting. Interesting, for me that is. But I often find testers struggling to frame their value beyond “I find bugs” or “I help mitigate … Continue reading
Here I’m not speaking to the people who are interviewing for roles in automation. I’m speaking to the people hiring them. The interview process is entirely broken in so many places. According to Eric Elliot, code-based interviews have always been … Continue reading
Lately I’ve been seeing that the whole “testing” vs “checking” debate is now more used as a punchline than it is for any serious discussion around testing as an activity and tests as an artifact. Regardless of my perception, which … Continue reading
The question of this blog title comes up often. The worst answer that can be given is: “When there are no more bugs.” It’s the worst answer because the inevitable follow up is: “But how do you know?” On the … Continue reading