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Showing posts from December, 2020

Trust Us: Push, Publicise, and Punish

In the recent peer conference organised by the Association for Software Testing and BCS SIGIST we asked ourselves the question Should the Public Care about Software Testing? I summarised the presentations in Who Cares? a couple of weeks ago and now the AST and SIGIST have published a joint report which manages to pull together and contextualise both the presentations and a whole day of conversation into a coherent whole. The report outlines a number of risks around contemporary software development that it's thought the general public are largely not aware of, but suggests that people should only need to care about software testing to the extent that they can trust that experts have exercised good judgement about where, what, how, why, and when to test.  It goes on to propose three categories of approach for establishing public trust — push , publicise , and punish — where pushes are applied up front to influence behaviour during the devel

Exploring to the Choir

I attended Rob Sabourin's talk Experiences in Exploratory Test Automation for the Test Tribe this morning. If I had to summarise it I'd say something like this:  it is a myth that exploratory testing cannot exploit programmable tools exploratory testing is deliberate learning using whatever tools are appropriate automation in exploratory testing can be one-shot, just good enough, targeted at learning Rob is preaching to my choir , and I've written about ways that I combine exploratory investigation with automation many times over the years, for example: But is it Automation? UI Testing Excellence Migrate Idea The Honest Womaniser Geek and Ye Shall Find Maaret Pyhäjärvi has long been an evangelist in this area and, while we're here, take a look her Intersection of Automation and Exploratory Testing presentation where she demos exploratory testing using

A Remote Possibility

  Last year, in the days before SARS-CoV-2, I wrote a guide to peer conferences for the Association for Software Testing . It didn't mention running a peer conference remotely. This year, I found myself setting up a peer conference between AST and the BCS Special Interest Group in Software Testing which had to be run remotely. Much of the guide still holds, and in some respects organisational concerns are simplified without travel, accommodation, and catering to worry about. But — and it's a Sir Mix-a-Lot -sized but — we've all done enough calls now to understand how hard it is to get the vibe right during a lengthy video meeting with more than a couple of participants. So what did we consider, what did we do, and how did it work out? On the purely logistical front, we had a few decisions to make. AST and BCS have worldwide memberships so choosing a time that didn't disadvantage some members was impossible. In the end, we ran

Plan, Do, Something, Act

Last night I attended a Heart of England Scrum User Group meetup where Mike Harris was asking So where did all this agile stuff come from? Luckily he was answering also: W. Edwards Deming . Mike's presentation was a high-level overview of the history of Lean and Agile in which he traced back to foundational work done by Deming and then to Deming's influence Walter Shewhart who integrated scientific methodology and statistics into industrial quality practices. I have read a little Deming but I'm motivated to look more deeply after this. In particular, Mike drew attention to the fact that Plan, Do, Study, Act and Plan, Do, Check, Act were, for Deming, very much not the same thing. I had never realised this.  The paper Circling Back: Clearing up myths about the Deming cycle and seeing how it keeps evolving by Ronald D. Moen and Clifford L. Norman talks about the strength of Deming's feeling about it, quoting him: The

No Shitcumber

Tonight's Atlanta Quality Assurance Association meetup was an interview, of Harry Collins by Michael Bolton , on the topic The Impact of AI on Software Testing. Collins' definition of artificial intelligence is "the ability to pass a demanding Turing Test." This kind of test requires knowledge of, and reasoning about, the society in which the dialogue is taking place. He gave an example from Roald Dahl's Big Friendly Giant where snozzcumber is considered an acceptable name for an imaginary vegetable, but shitcumber probably wouldn't be.  That may seem obvious to us, but on what basis would a machine learning algorithm fed tons of textual data, perhaps scraped from the chaotic mess that is the internet, be able to tell? He relates this question to his taxonomy of expertise in which interactional expertise is what gives a conversational participant the language of practice — so much more than simply words and grammar — of their community. Although it's