Some philosophical / math explorations, with a sidedish of empirical data, and a (hopefully) useful point of view you can borrow.
https://t.co/lfVi1oPesA
New post on the blog:
What the surprise exam paradox (and Gรถdel's theorems) has to do with a green risk register, why the 15% buffer line is a category error, and why "we'd have found it by now" is the most expensive sentence in project management.
We'll do an overview of Wolf's wonderful work, and use it to examine what "testing saints" would look like, and how they ultimately fail themselves and everyone around them.
https://t.co/vBXmpEERs7
#philosophy#testing#moral_philosoph
New blog post, this time using Susan Wolf's "Moral Saints" to give you a rigorous, well structured, academically respectable licence to hate your coworkers. What could be better?
@jhartikainen Maybe bug free, but not defect free I would think. Just that the deviations from spec there have been instituted as known issues.
What do you think?
I agree that where changes occur, unacceptable defects flot to the top ๐
New blog post, harnessing the anti-rational, amphetamine fuelled philosophy of Nick Land to celebrate the under-utilised practice of exploratory testing.
It's gonna be lots of fun (and lots of rats, as Land is... special that way)
https://t.co/KRgT8C2MHm
New post in the blog, asking whether GenAI can be said to know anything, from an epistemological point of view.
First we build a toolbox: the classic definition of knowledge, the ways it failed, and the concept of sensitivity that came out of the wreckage.
Yes, you've probably read 3 posts asking the same question this month alone, but we'll try to examine it from a philosophically heavy point of view which will (hopefully) be refreshing.
https://t.co/mjnpkULOkb
#philosophy#ai
Then we borrow from evidence law to turn the abstract into something more concrete. Armed with that, we unpack "does AI know" into terms you can actually argue about, and argue we shall.
@jhartikainen Thank you very much ๐
Yeah, he's very relatable and lends himself to a lot of practical systems and situations.
No wonder he's quoted in pretty much every major field of thought ๐
Time for the 2nd part of our Kuhn series. We used part 1 to build an understanding of Kuhn and explore how it maps to the modern software testing setting.
This part adds some much needed nuance through post-Kuhnian thought, that will allow us to extract more actionable insights.
We'll offer a more detailed mapping between the philosophy and software testing, and use this context to explore the debate for and against method and practice.
Oh, and there's the obligatory GenAI take as well, naturally.
https://t.co/lWND2CnHlE
onto the modern software industry, and attempts to derive some non-trivial insights.
Vanilla Kuhn sets the stage, but it will take the more nuanced post-Kuhnian discussion in part 2 to extract some actual action items.
https://t.co/hTnfmf37jG
Nobody learns testing from principles. You copy the shape of existing test cases and keep copying it for three years. That's a paradigm, and it's why the test suite is the last place a wrong model ever shows up.
The first of a two-parter in the blog maps Kuhn's philosophy
Launched a draft version of my new website, where I'll explore software, testing, and software testing though a philosophical POV.
Expect long form content, not for the faint of heart.
https://t.co/gs7koO1EIs