Why Have You Stayed in Testing?

I get asked this a lot. I’ve been doing some form of testing since the early 1990s and while my initial opportunities were provided by chance, my career was one of choice. Rather than say why I stay in testing, I’ll frame this around some questions and answers that may give some insight of how testing has allowed me to answer certain questions in a career-relevant way.

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Framing Automation-Based AI

I recently talked about a focus on being able to test an AI before you trust an AI to test for you. Here I want to provide a bit more focus on how worth it this idea might be. But my goal here is not to dampen the spirits of those who want to build such tools; rather I want to suggest some of the challenges and provide a bit of the vocabulary. I want to give you a way to frame the current situation with AI and its value as a test-supporting technology.

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Testing AI … Before Testing With AI

A lot of testers are talking about how to use artificial intelligence (AI) or machine learning (ML) to be the next biggest thing in the test tooling industry. Many are in what seem to be a lemming-like hurry to abdicate their responsibilities to algorithms that will do their thinking for them. Those same testers, however, often have absolutely no idea how to actually test such systems in the first place. So let’s dive into this a bit.

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The Constraints of (Testing) History

As a specialist tester, one has been doing this since the early 1990s, it’s interesting to follow the contours of a notoriously fractious discipline. A discipline that is often populated by articulate but frustratingly argumentative practitioners. I say “frustratingly” not because argumentation is bad (it isn’t) but because that argumentation often turns into becoming an instinctive contrarian and a ruthless, rather than pragmatic, skeptic.

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An Ode to Testability, Part 5

In the previous post we ended up creating tests with a context. And that context was allowing us to bridge the gap between correctness and value while also continuing to put focus on testability. We saw some warning signs along the way but, overall, made progress. Here we’ll continue that progress and also start to see how while testability is something to strive for, just doing so by itself guarantees us very little.

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