Part of achieving quality in software means treating testability as a primary quality attribute. Once you do that, you can then adapt your requirements and development styles from that point of view. Whether you call that “agile”, “lean”, “scrappy” or whatever else is largely beside the point. The focus is on testability. But let’s talk about what that means.
Like most disciplines, testing has some so-called truisms that get passed around, many often being blindly accepted. The problem is often that our discipline requires a bit of nuance that the truisms — even if accurate — tend to gloss over. So let’s dig into a few of these.
I personally think the answer to my title question is an obvious “yes.” But I do see a lot of discussions about how the DevOps movement and/or culture has “killed” testing or has removed the need for testers. Let’s talk about that.
There are groups of testers out there right now denying that the term “manual testing” — or the reality of the term — does exist or has ever existed. To me this is a bit of historical revisionism. Let’s talk about this.
I talked before about tradition and dogma in the testing field. It’s often interesting to see how the idea that get passed off for wisdom in the testing world come about. Let’s take one example and break it down.
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.