#270 – But what if we can’t release often?

With digital solutions there is a ongoing urge to release often. A quest for feature toggles and continuous deliveries of new features and fixes. Automation of tedious tasks do help to drive consistent deliveries and aids in driving high-performing teams. There is good research to support that.

Recently I have worked on a solution, where the system had only to work for a month each year – and be closed down the other months. Some solutions I have similarly looked at, have years between being active. We can’t wait to ship features in the next release – the system has to be at 100% features that specific month.

Examples of business situations and domains:

  • Performances, like Eurovision
  • Sport events, like the Olympics
  • Elections
  • Black friday, Christmas shopping?

How do you test when you can only perform the act once – and if it fails it will have serious consequences? You practise and rehearse until it becomes safely repeatable. You have stage-moms and support teams to train with you.

Let’s look at the ultimate example: rock-climbing with no rope. How do you test for climbing up Yosemite’s El Capitan 3000 feet / 900 meters?

Photo by Tobias Aeppli on Pexels.com

The accomplishment is more preparation than performance. Honnold climbed El Capitan roughly 50 times in the decade before his free soloing of the rock formation on July 3, 2017. While he is famous for the ridiculously fast 3-hour, 56-minute ascent, 99% of Honnold’s time on the wall was spent roped up, practicing the route. Knowing where and how to move was the culmination of hundreds of hours on that granite in advance.

The Seven Lessons From ‘Free Solo’ On Working Without A Rope

Besides the scaling of the IT infrastructure for peak load – the test strategy has to consider the fact that the event itself will be a one-off, where there show must go on – and there’s no fallback, only fall forward.

There’s a huge difference between continuously delivering web features every day in a business to consumer setting, as compared to one-off projects of migration legacy platforms. This is why my approach to creating situational aware test plans starts with looking at delivery speed:

RareRegularOftenPervasive
One-offQuarterlyWeeklySo often you dont notice
A scale of delivery speed

In one of the projects I looked had we had extensive user rehearsals and dress rehearsals. Well, they are called something more IT fancy. But at the end of the day it was about training to make the performance muscle knowledge in the people performing the event. Much like the training Honnold did.

Lastly, my experience is that you get more organizational traction by aligning with goals rather than risks and issues. It’s a behavioral trick simply to talk about the thing you want to give attention. And at the end of the day the CEO wants to talk about goals rather than risks. She rather wants a successful performance with a few flaws that an delay due to bruised hands (and egos) during waxing on and waxing off.

#265 – Using MTTR to Understand When to Test

It interests me deeply to explore why testing is happening. Often it’s because some decision-maker or framework dictates – “This is the Way“. And off we go on the quest to slay the dragon – or move items from point A to point B. Without much thinking about how the side quests help to move the main risks of the story.

The main risks are usually around something irreplaceable – and hence we test and try our best to shield it. But not all risks are equally dangerous. In IT we can build implicit testing into repeatable deliveries and reduce the time to fix things. The faster things are fixed, the better is time to information for the business needs.

Grogu agrees
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The Testing, not the Testers

Occasionally I see posts and discussions, where testers are indignated that this and this company has no testers. How could they! Or similarly when a product is released publicly with significant issues: See – it’s because they have no testers! Or that the testers are not taken seriously. OMG!

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Closing the Gaps

[Previously on the Ministry of Testing, Nov 2014 – now only on the Web Archives]: About Closure

When I’m in a testing activity I want my test cases [Passed], my user stories [done] and my coffee [black].  Stuff may have a start point, some states in between and an end state. Lets look at ways to represent states and articulate the meaning of states.
One way to illustrate status about the product being tested is to model the activities we have with states. An agile user story may be [ready], [in progress] or [done]. A document may be [final], [approved] and a mind map may be iconified etc. States are so common that we sometimes forget the theory behind the model, and what benefits we have from the theories.

The representation of closure

For instance we can look to computer science graph theory[1]  to help us understand and control the states diagrams. It is the same graph theory that brings us state machines and state-transition diagrams, but that is another story[2] . In a graph theory state model we want one unique start state (Like [To do]), and one unique end state (like [passed]), everything in between is intermediate.

A (single) end state helps prevent the state machine from going on forever[3] , and us from going on forever too. [Deferred] and [Rejected] are temporary states to me. Setting [Rejected] back to “detected by” will aid that the tester reflects on the reasons. The reasons are then tested (in the brain). Sometimes it’s a “my bad” but quite often also the tester finds that issue is simply not “rejected” with more data and examples.

The understanding of closure

Similarly the agile “Definition of Done”[5]  and “Definition of Ready”[6]  helps the agile team phrase when the task is to change state, sometimes it’s explicit, sometimes it’s implied. The understanding of terms (the semantics) are usually more imperative than the syntax (the rules and representation). Sometimes it’s necessary to “connect the lines”.

There are a two related psychology theories on closure. One is the Gestalt law of closure[7]  – that is that we tend to self-organize items into an orderly structure. As the image above isn’t really about triangles – it’s about our human tendency to connect the dots. The other psychology part is the desire to close stuff to gain controllability[8]:

The need for closure is the motivation to find an answer to an ambiguous situation. This motivation is enhanced by the perceived benefits of obtaining closure, such as the increased ability to predict the world and a stronger basis for action.

Management and stakeholders often want a “firm and unambiguous” answer from our testing investigations. And this is often the business justification for setting states to our work products; that we have states to illustrate work progress in. Sometimes loose representations and a strong shared understanding goes well, sometimes a more strict representation and elaboration is required.

The syntax of states may be easily explained and codified (and checked), while the semantics and perception is less direct – and needs analysis (and testing). All work products (even for mind maps and test charters) have states and we must articulate both the syntax and the semantics to the team and stakeholders.

References

  1. Graph theory http://en.wikipedia.org/wiki/Graph_theory
  2. Fell in the trap of total coverage https://jlottosen.wordpress.com/2012/11/05/fell-in-the-trap-of-total-coverage/
  3. Finite state machines http://en.wikipedia.org/wiki/Finite-state_machine
  4. A Track down History
  5. definition of done https://www.scrum.org/Resources/Scrum-Glossary/Definition-of-Done
  6. definition of ready http://guide.agilealliance.org/guide/definition-of-ready.html
  7. Law of closure http://jeremybolton.com/2009/09/gestalt-design-principles-the-law-of-closure/
  8. Closure (Psychology) http://en.wikipedia.org/wiki/Closure_(psychology)