Transforming your Software Testing to fit the modern ...

Copyright© 2019 Sogeti. All rights reserved.

Transforming your Software Testing

to fit the modern organizations of

the future.

Author: Fredrik Scheja


Michelangelo said, at the age of 85:

“I am still learning.”

It is often said that we learn from our mistakes - or the importance in business

to fail fast. I personally only partly agree on that. I think we learn from all actions in fact, as long as we keep on trying out an idea - continuously testing hypothesis. Our ability to learn rest on our ability to reflect on the outcome, the

results of our intended actions. I'll never stop learning and I write primarily for my need to test my mental models on you, the reader, and possibly see what

outcome and effect it might have on you. So please get back to me if you have any sorts of feelings, thoughts or reflections on what I have to say. I want to explore this subject together with you because it is more fun to do things

together and I know I learn more through dialogue with others.

I would like to tell where I strongly believe software testing is heading. This, in order to shine some light into the various trends I see in the industry both from

a historical aspect as well as in the future. We come from an industrial age, where transactional test has been our way-of-working historically. What do I

mean by transactional test? It means that we have been focusing a lot of the actions we do, the documents we create, the checklists we follow and the interactions we establish. Our entire software testing world has been orbiting

around the process, the routines, the tools we use as if they should solve our problems and issues.

But guess what? We are humans and placed here on earth for a higher purpose.

And this is exactly why we now need to indulge ourselves into the transformational era - for real. We need to transform our way to plan, talk, educate, design and how we perform and how we recruit within software testing.

I know - the transformational phase might seem dangerous at a first glance, but if we embrace it we´ll develop our self and our abilities to think, act, see and

move faster but at the same time feel stronger, more confident in ourselves and rest assure that we´ll offer more value with less energy. The journey might feel scary sometimes and we might feel lost, because it mandates letting go of our

current mental models and the way we picture our self - but trust me, it is necessary. The way we have been operating will not scale, it is not sustainable

to work the way we've been working and it is only a matter of time until the system collapses. The fourth industrial revolution is building up momentum –

fast.

I use models in my line of work and I love models - it helps us to grasp complex matters. Here is one I've inherited from ‘The Digital Happiness’ report series from SogetiLabs.


Originally, the model explains how we consume products and services, but I’ve added an additional layer to it to explain it from a development organizational

process-perspective. Most organizations have left the warm and cozy factory-based transactional development processes where resources were seen as cogs in a complex waterfall-like machinery. The problem with these organisational

setups were that they performed very slowly. The software development organization is seen as a factory that mass-produces software on a large scale.

The setup is best utilized when the requirements for software is static over time and identical from all aspects of end-user perspectives, which is rarely the case in reality.

Agile development methodologies of various flavors have therefore become

popular and are all grouped together in this model as transformational development approaches because what they all have in common is an aspiration

to transform a transactional development model into one future state – the authentic organisation. What is an authentic organization? According to the elevator pitch made by Celia V. Harquail: 'An organization is authentic when its

actions, its character, and its sense of purpose are aligned with and support each other. An organization can be authentic only when:

• The organization knows ‘who it is” and what characteristics make it

distinctive. People in the organization understand why these distinctive features are meaningful.

• The organization knows what it is striving to create in this world. It has a sense of purpose that goes beyond the products and services it offers.

• The organization knows how its distinctiveness fuels and adds

unique insight to the pursuit of organization’s purpose. • The organization has a few signature actions, behaviors and products that

bring to life the organization’s meaning, and move it towards its purpose. • Both the purpose and the distinctive, meaningful characteristics of the

organization resonate with stakeholders and draw members, customers,

and constituencies to the organization. • The organization actively supports its members, customers, and

constituencies in their own authenticity as they work with the organization to achieve its purpose.'


This state could also be explained through the words of our agile syntax – when

the idea of autonomous team has distilled down and transformed into the autonomous individual. When each individual in the organisation have a deep understanding of the business goals and how their personal mission and actions

relate to these goals. The individuals are also highly self-confident and aware of their own individual ethics and values – which then of course matches the

organisation you work from within. This has the capacity to create an enormous flow, creativity and innovation due to the fact that we all are aiming for a joint vision.

But what do we need to do in order to get there as entire organisations? What do we need to focus on, what do we need to learn as individuals, and as a group and business? In order to enable this change at scale we are today focusing a lot

on technical aspects like operational AI, automation, big data and more people-focused trends like data-driven decision-making, experimentation, servant

leadership and so forth. But what will happen after robots really actually help us doing the transactional tasks? In the industry today, it is said that the need for people with high Emotional Intelligence (EI) will most likely develop into a 'must-

have'-skill for most businesses within the upcoming five years. This means that the market expects intelligent automation and robotics in our organisations to

enable humans to focus more on our self- & social awareness and our self- & relationship management. But does this mean that we all need to become socially skilled experts? No, I don´t think so, but I think that the balance will

shift gradually so that people with Emotional Intelligence will become more frequent in our teams and they will ask the necessary transformational-focused

questions more often - enabling us all to become more self-aware on what factors we need in order to feel good.

But how do this relate to software testing? Firstly, it'll be necessary to change how we look on software testing; from the transactional view as a process that

should filter out the bugs into seeing it as an enabler of new insights and learnings. This is a paradigm shift for software testing in its core because we

need to provide these autonomous developers in this highly effective organisation with decision support in order to enable smart, hyper-fast decisions based on intelligence and authentic information rather than guesses and faith.


Because, as an effect of these fast-moving organisations - also according to

Conway's law - the system landscape will be continuously re-shape and transform in a hyper-fast way. In order to keep this up we need to look upon how we enable these kind of organisations with information on all kinds of

software-related quality-focused aspects.

What would people need to know? What kind of information would they

appreciate? Would it be possible to know before-hand? In some cases yes; in many cases no. We need a new narrative of testing in order to better understand

how to approach and tackle this new paradigm because our current mental models are not even closely enough.

The five hops of Software Testing

In the book Testing in the Digital Age, by Rik Marselis et al. Five 'hops' of software testing is introduced:

1. Automation and Robots

2. Use the Data 3. Go Model Based

4. Use Artificial Intelligence 5. Test Forecasting


I believe in this model, but I don´t believe these hop will be taken sequentially, I´m certain they will have their own hype that is slightly shifted in time, and

even the order of these different 'hype-hops' is going to be interesting to see when they come. I recon these hops will be accompanied by a great deal of cool buzz-words, looking forward to see what they might be. I believe we are

currently in the first hop. The market is nowadays screaming for automation experts and implementing robotics everywhere. Buzz-words are clearly Robotics

Process Automation, Articifial Intelligence and Machine Learning. Soon we will enter the second hop where the beauty of development/QA-related data will be widely understood. This is when test automation is going to be seen as a data

provider instead of a bug filter. But the data will make us painfully aware of the fact that the complexity of our system landscape far exceeds our wildest

imagination. So we enter hop 3 - Go Model Based. Here I foresee that we understand that we'll have to start look upon models in a higher abstraction perspective. An architecture model consisting of boxes and lines between

systems are merely not a scalable model. We will have to start looking outside of our own engineering craft and get interested into more complex areas of

measuring and information gathering from other industries and sciences. When software increase in complexity and scale it starts to take another form, a form

that more resembles a living organism than a static, mechanical machinery. Because - let's face it - the idea of trying to maintain a decoupled architecture is a nice thought and a good practice in theory to a certain extent, but guess what?

At some level the different digital components will have a dependency towards each other, it is inevitable. So why not just embrace it? Embrace the fact that

your architectural model is complex and it is only going to get worse?


If we embrace the complexity of our digital platforms we force ourselves to start considering them from another perspective; as a digital creature continuously

evolving on its own and operating between the analog (mechanical) and biological (human) realms. When our simplistic mental models inherited from the industrialized mechanical world is not enough anymore, we need to adhere to a

nomenclature and approach originating from other sciences, for example biological or even behavioral neuroscience. We need to look upon our system

landscapes as continuously evolving digital organism and start testing based on this new narrative. This is when our test automation starts to be perceived by us as 'sensors'. We will start deploying a massive number of sensors in our

applications, environments and business applications in order to gather data streams from our digital landscape. This is like connecting our "digital patient" to

a heart and lung monitor system in order to increase our ability to extract insights to "treat our digital patient". So what kind of data do we look for? Sometimes we know, sometimes we don´t - so we need to gather this data in

big data storage in order to test our hypothesis on and detect and foresee correlations, patterns, dependencies and interesting trends that we can extract

important insights from. In bio-science these insights are often referred to as bio-markers:

‘a naturally occurring molecule, gene or characteristic by which a particular pathological or physiological process, disease, etc can be identified.’

So, in a modern test strategy, we need to start including various approaches to deploy sensors and exploring around what we might refer to as ‘technomarkers’ – signs of concerns that might lead to failures, intrusions, unexpected usage or

degradation of various kinds.


Does these transition mean that we need a new set of tools? No - I don't think so. A sensor can be implemented using the technological toolbox we already

have, for example jMeter, python or any other script-language. It is perhaps even the same test scripts we've implemented since before, it is just a matter of

how we utilize and perceive the scripts and how we put them to use. We will perhaps start by executing our business-critical smoke test in containers everywhere throughout our system landscape instead of manual or development

pipeline-triggered scripts just because "we need the data".

When we start getting used to collecting data streams together and look for various interesting patterns I would like to refer to this not as software testing,

but rather Development Intelligence. We will then start experimenting even further with machine learning in our quest for knowledge and it will develop into

more advanced forms of artificial intelligence. Enter hop 4. This is when AI matures and our system landscape starts to get injected with a lot of self-learning and autonomous bots. When we hit this stage in our development we

will get aware of the fact that we have developed a system landscape that is so complex that we don´t even know how it is set up any more and it is developing

- evolving - itself. At this stage it is good that we developed our own abilities within Emotional Intelligence, because we now need to be able to express models for ethics, morale, responsibility, ability to learn, cognitive intelligence.

And - we need to be able to express these models in code and teach our systems these abilities. How do we test a digital organisms' ability to be ethical?

What is the true difference between accountability and responsibility? Working with QA in this era will surely resemble how to be a parent or a pre-school teacher that constantly make sure the systems learn new things but provides

them with opportunities to fail in controlled surroundings.


Hop 5 - Test forecasting. At this stage I think the term we know as ´Software

Testing´ is made extinct. Somewhere in the course of events testing has become totally submerged into developing. We've created sensors that offers data streams in order for us to understand complex events in our system landscape.

Then we started to feed these data streams to our development bots to take corrective actions for themselves. When these bots indicate a significant

technomarker or any other interesting events this event instructs another bot to learn something new based on this event and create a new digital mutation in order to learn from this new experience that creates another significant event

and this happens during a couple of milliseconds, you see where this is going? Humans won´t be able to keep up. End users will be able to use digital tools that

will look slightly different each day based on last days usage, the system will analyze the current usage and business metrics and continuously adapt itself in

small iterative manner.

How do we prepare for this transformative journey as developers and testers?

Once we've realized that software development and testing won't be the same in the future, we must go out and get interested into how we measure and gather insights from various other sciences. How do we capture brainwaves? How do we

track neuron signals through our synapses? How is our central nerve system built up and how can we track, monitor and find early indications that there is something wrong? What is the latest innovative discovery within sensor

industry? How do we extract data from such sensors? I strongly believe these are the questions that prepare you and your organisations for the testing aspect

within industry 4.0.

References:

I´ve gathered lots of inspiration from In Persuit of Digital Happiness Report series: https://labs.sogeti.com/pursuit-digital-happiness/

First time I heard about technomarkers were from Anders Källström from the

Sustainability Circle - read their manifest here: https://www.sustainabilitycircle.se/manifesto-short-english-version

Testing in the digital age - https://www.ict-books.com/topics/digitaltesting-en-

info by Rik Marselis, Tom van de Ven, Humayun Shaukat

https://labs.sogeti.com/pursuit-digital-happiness/

https://www.sustainabilitycircle.se/manifesto-short-english-version

https://www.ict-books.com/topics/digitaltesting-en-info

https://www.ict-books.com/topics/digitaltesting-en-info


About Sogeti

Sogeti is a leading provider of technology and engineering services. Sogeti delivers solutions that enable digital transformation and offers cutting-edge expertise in Cloud, Cybersecurity, Digital Manufacturing, Digital Assurance & Testing, and emerging technologies. Sogeti combines agility and speed of implementation with strong technology supplier partnerships, world class methodologies and its global delivery model, Rightshore®. Sogeti brings together more than 25,000 professionals in 15 countries, based in over 100 locations in Europe, USA and India. Sogeti is a wholly-owned subsidiary of Capgemini SE, listed on the Paris Stock Exchange.

Learn more about us at

www.sogeti.com

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