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DevOps and Software Testing.

Most of my recent work has been with DevOps teams. While in one sense DevOps is another evolution in software development. It also introduces some new skill requirements and responsibilities into the daily routine of a tester.


I've created a short video to highlight some of these changes and the opportunities they bring. It's not an exhaustive view of DevOps but it gives a highlight of what you could be working with.


While DevOps isn't a panacea to our software development problems, I have found that empowering teams with the ability to build and use the tools they need, can rapidly improve team morale and productivity.

Unicode Babel

I've written about the joys of Unicode and software development before. Using unexpected data in your testing is usually a good way to test for text encoding issues. Finding and fixing these those bugs early could save your team from a host of other related issues and hackery.

Even if you don't expect to have unusual text content, this type of testing can help indicate if all your systems are configured consistently. Failure to do so can result in users seeing the dreaded Mojibake.


I've recently created a python package for generating random Unicode codepoints so they can be incorporated easily into your automated tests and tools. It's called Unicode Babel, and can be used to create a simple iterator for supplying 'international' text to your app:

from unicode_babel import tools, filters genny = tools.CodePointGenerator() for point in genny.random_codepoints(10, filters.filter_out_if_no_name) print(point)
Will output something like:
ᓆ ᗡ ꋛ 販 ۅ 䶣 楨 蟷 䔉 ݥ Or …

As near as damn it.

It's 1982 and there's a bull market in the western stock exchanges. After being in the doldrums for 6 years the Dow Jones Industrial Average index is climbing steeply. In London, the FTSE 100 index is also witnessing a steady climb, despite the ongoing war in the South Atlantic. The rise in share prices also leads to an increase in the popularity and prominence of these stock 'indices', the algorithmically derived snapshots of leading stock prices, frequently, used as an indicator of overall market health.

At that time a relatively small North American exchange decides to institute its own new index, allowing investors to discern, at a glance, the state of the market. The Vancouver Stock Exchange creates its index at an arbitrary 1000.0 starting value. The index value is then recalculated thousands of times a day as transactions are processed through the exchange.

Fast forward to late 1983, western markets have continued to boom, stimulating sustained increases in the…

Testing a maybe with machine learning.

“I figured it was just a jumbo jet.”

My son and I shake our heads & then adopt blank stares as if a non-body-snatcher has been
exposed in our midst.
“Twin engine,” I utter, as I glance skyward again.
“Single decker” My son adds as an explanation.
“It’s a plane”, she retorts, rolling her eyes.
My wife, (who is far smarter than myself) lacks my son and I’s ability to recognise aircraft. She has the typical persons ability to recognise aeroplanes. I grew up around airforce bases. I had a father who was an aircraft engineer. Years of exposure and explanations regarding aeroplanes, their mechanics and features.

My son is an avid flight sim game player and has consumed many hours of relevant youtube material on the subject. He also had the luck/misfortune of me discussing the planes that frequent the skies, above us here, near London.
Given our combined experience & expertise, we probably have a reasonable ability to recognise the make & model of the planes we see in the sky. I would h…

Betting in Testing

“I’ve completed my testing of this feature, and I think it's ready to ship”
“Are you willing to bet on that?”
No, Don't worry, I’m not going to list various ways you could test the feature better or things you might have forgotten.
Instead, I recommend you to ask yourself that question next time you believe you are finished. 
Why? It might cause you to analyse your belief more critically. We arrive at a decision usually by means of a mixture of emotion, convention and reason. Considering the question of whether the feature and the app are good enough as a bet is likely to make you use a more evidence-based approach.

Why do I think I am done here? Would I bet money/reputation on it? I have a checklist stuck to one of my screens, that I read and contemplate when I get to this point. When you have considered the options, you may decide to check some more things or ship the app. Either could be the right decision.
Then the app fails…
The next day you log on and find that the feature is b…