I see a lot of vocal pundits in the testing world saying that artificial intelligence (by however they choose to define that) is no threat to future testing. I’ll ignore for a moment that most of these pundits get AI wrong — equating it, as they do, with “better algorithms” — but I won’t ignore that they seem to forget a key point: will there be a perception that AI can handle future testing?
There is a distinction between “being a programmer” and “being a developer.” Yet those two terms get conflated in our industry quite a bit. The idea of a tester also gets conflated with … which? Programmer or Developer? That very much depends. Combine what I just said with the idea that many testers feel that DevOps has caused a decline in testing. Is there a correlation there? And should testers become developers? Let’s talk about this.
There is still so much wrong with how testers — even those who will write automation — are interviewed. I talked about this already regarding how technical test interviews are broken and about interviewing technical testers more broadly. Is there really more to say? I think so; let’s see if you agree.
There’s a book I really enjoyed that I believe every tester should read. Actually, anybody who has to communicate should read it. The book is called Don’t Be Such a Scientist by Randy Olson. And it talks about the need to have effective means at communicating by framing issues in a way that is interesting and not just recitations of things that people have been doing or saying. Let’s talk about this.
There is a relatively common sentiment that tester roles, as opposed to the testing activity, should disappear entirely. We see that a bit with descriptions of jobs like “Software Development Engineer in Test” (SDET) which basically just means “developer who can test” rather than “tester who can develop.” Is this evolution necessarily an unhealthy one? Let’s talk about this.
The title of this post indicates a sentiment you’ll often see. “Testing is the art of …” and then fill in some word or phrase. While I get the intent behind this, the word or phrase used to complete the sentence is often a bit lacking and actually reinforces the opinion that many have of testing, which is that it’s not a distinct enough discipline.
This post is the last in the data science series (see 1, 2, and 3). Here we’ll wrap up the entire discussion, including whether we actually discovered anything about our initial question regarding “Which is the best Pokémon character?”
This post follows on from the first and second posts. Here we’ll continue the theme of our Pokémon data, this time working at getting some more specific answers to our running question in this series: “Which is the best Pokémon character?”
This post follows on from the first. Here we’ll focus on the skill of interpreting our Pokémon data so you trust the data enough to make decisions based on it. This is fairly important if you are a tester working in any context wherein actions against data will be presented to you or where you have take those actions yourselves as part of the testing.
I’ve talked a bit about testers and AI as well as testers and machine learning. Here I want to focus a bit on one area that can be a basis for both of those areas: data science. As a tester, you don’t need to be a data scientist. But it certainly doesn’t hurt to have a grounding in what data scientists do. Here we’ll do some exploratory computing with Jupyter; we’ll use some numerical and visualization libraries and we’ll explore the (fascinating?) world of Pokémon data. So let’s take a few posts to dig into this.
What do people tend to think of when they hear “tester”? More specifically, what do they think a person called “tester” primarily does? Arguably, more often than not, you’re going to hear something like “a tester’s role is to find bugs” or “a tester helps surface issues.” As an approximation, that may be accurate. But it’s only a very rough approximation. And a dangerous one. So let’s talk about this.
As part of my attempt to continue my thinking on the topic of “tests” and “checks”, I’m revisiting what I talked about previously. I want to see if my thinking has changed and I want to set myself up for being willing to change my opinion. I don’t want to be one of the fundamentalists I wrote about. So let’s take another trip down the rabbit hole.
I believe there’s an interesting parallax effect that happens in conversations around testing and the implementation of testing ideas. This is an area I want to investigate a bit more so I’ll start off as I usually do: with my half-formed ideas as the basis for discussion, elaboration and possible refutation.
… but you may not be a tester. Or at least not a specialist tester. Here I’ll close out 2017 on this topic which will indicate some of my future direction in 2018.