Testers and Future Angst

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?

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Should Testers Become Developers?

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.

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Don’t Be Such a Tester

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.

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The Evolution of Testing

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.

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Testing Is The Art Of …

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.

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Testers and Data Science, Part 1

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.

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Testers and the Bug Hunting Focus

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.

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