In the last two years a number of unprecedented events have dramatically changed the world; we are not referring to software methods and technologies (Agile, DevOps, Shift Left, etc) but rather to much more pervasive events likewise: COVID pandemic; international wars and their political as well as economic impacts; the Great Resignation and the evolution of work habits; the climate changes and the growing awareness of the importance of “Green IT”; the increasing penetration of process automation and AI

Which are the impacts on Software Quality and certification of competences?

What can we expect for the next future?

The speech aims at addressing these fundamental topics, trying to identify good practices to transform risks into opportunities

Misunderstandings between developers and the business are a plague. Bad communication makes projects fail. This talk presents a remedy (including a practical demonstration with auditorium participation).

Domain Storytelling is a technique to transform domain knowledge into effective business software. It brings together domain experts and development teams to: (a) understand the domain of a software system, (b) find microservices boundaries, and (c) talk about requirements.

We let domain experts tell us stories about their tasks. While listening, we record the stories using an easy-to-understand pictographic language.

The domain experts can see immediately whether we understand their story correctly. After very few stories, we are able to talk about the people, processes, and events in that domain.

The talk is aimed at everyone involved or interested in software development, including non-technical people.

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"You can't test quality into a solution" is almost a platitude in software development. In my experience, however, there is a lot of truth in it. But how do you achieve quality at all? There are many approaches to defining quality in norms and standards. These approaches really help to understand what quality means for software, but they do little to help achieve quality. I think quality starts with the right attitude. For software, the 10 theses for good digital design are an expression of the right attitude.

In my talk I present the 10 theses for good digital design and show that digital design and testing have to be essential partners to achieve real quality.

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Following on his presentation, you will explore what Quantum Testing can mean for now and more importantly for the future. As this is not an established discipline, you will not be taught Quantum Testing but rather explore insights and challenges faced in Quantum Testing

We all know that projects, trying to “test quality into a system”. fail! That’s why the first step to build high quality products, systems or services starts in Requirements Engineering.

Requirements are the food for thought for testers to come up with well suited test cases to ensure that the delivered solution serves the desired purpose.

But this is by far not enough – Requirements Engineers and Testers have to cooperate already in early phases, when setting the context or reviewing and validating requirements. Testers are able to provide meaningful input in order to specify requirements that are verifiable /testable.

To highlight that both parties are pulling in the same direction, we'll talk about which of the nine fundamental principles for good RE contribute to testing.

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We all know that projects, trying to “test quality into a system”. fail! That’s why the first step to build high quality products, systems or services starts in Requirements Engineering.

Requirements are the food for thought for testers to come up with well suited test cases to ensure that the delivered solution serves the desired purpose.

But this is by far not enough – Requirements Engineers and Testers have to cooperate already in early phases, when setting the context or reviewing and validating requirements. Testers are able to provide meaningful input in order to specify requirements that are verifiable /testable.

To highlight that both parties are pulling in the same direction, we'll talk about which of the nine fundamental principles for good RE contribute to testing.

It is not very often that new black-box test techniques are developed by researchers and prove themselves in practice. Metamorphic testing is such a case. It is particularly well suited when an adequate test oracle is not available. Instead of predicting an expected result for each test case, this technique checks whether the inputs and the results of different test cases are consistent with each other. The author introduces the technique with an own example, classifies it in the test methodology, and illustrestes its relevance with examples from information retreival and artificial intelligence.

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The testing job profile of the German Testing Board (GTB) is a reference for an adequate testing skillset in projects and organisations. It is intended as a guidance to meet current and future challenges to ensure software quality more effectively and was recently updated with a stronger focus on agile processes reflecting the current situation on the market.

The testing job profile will be presented and discussed together with and in the context of results of recent surveys in the testing domain the latter showing the current situation regarding major topics and challenges in testing to be addressed by an adequate testing skillset.

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The presentation gives a brief introduction into Artificial Intelligence (AI) with the focus on Machine Learning.

Starting from the ISTQB test process typical test activities are listed and it is discussed where AI can support the test.

Several practical examples are presented.

The presentation closes with an honest view on the situation as well as an exemplary listing of available AI-based test tools.

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The Challenges of Software Testing in Developing Economies – Case Study Nigeria The COVID-19 pandemic has defined a new normal. While businesses all over the world are transforming themselves to adapt to this new normal, the software industry globally is reaping the benefits of the season due to increased demand for technology.

In Nigeria, companies are starting to look inwards for their software needs which has now led to an increase in the demand and acceptance of indigenous software. We can boldly say that Covid-19 has opened a floodgate of opportunities for the Nigerian software industry and presented a gateway to emancipate the industry from the clutches of imperialism.

If Nigerians, including government, begin to buy from Nigerian software providers, Nigeria would have an industry that would internally generate over $2 billion annually and that alone would spiral into other. African countries, then to other countries all over the world. However, with all these opportunities comes the question of quality, “Are Nigerian Software Developed with Quality in Mind?”.

We are aware that some of the software developed by indigenous software houses in Nigeria do sometimes pose a huge quality challenge to both public and private organisations in Nigeria hence the low patronage.

To move forward, we must identify and track the bugs that may crash these opportunities presented by the pandemic and fix them to prevent this opportunity wave from fading. These bugs when fixed would build the required confidence needed to meet the demand of the industry.

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Artificial intelligence (AI) is now a mainstream technology that touches the lives of most of us, with a global market predicted to reach US$500 billion within two years. AI-based systems, and machine-learning (ML) systems in particular, are different from traditional IT systems, as the underlying code is not written by a programmer but is inferred from patterns in data. This major change to classic software development has two significant knock-on effects. It has created the attractive new role of AI specialist.

However, it has also created several new sources of specialised defects, such as the training data, the deliverable ML model and the ML development framework. This talk proposes a new software testing specialism that is focused on addressing the new challenges introduced by AI and ML.

To be able to test a ML system, testers need to understand the underlying technology and how it can go wrong. They also need to be able to address those system attributes, such as ethics and trust, which are so important with AI-based systems. From now on, as AI-based systems grow in complexity and criticality, achieving acceptable levels of quality and trust will only be possible by employing independent, AI test specialists.

This talk will explain why they are needed, what specialist testing they will do, and suggest how we should handle the transition to a future where the AI test specialist is a recognized role.

You can become a tester through multiple ways: e.g. with computer science background from university, through being a domain expert in some business, through additional testing studies at a re-education program, or just starting to test and learning by doing.

There are many ways, as there are also many skills needed in testing. No-one has all those skills to start with, regardless of the background. But can you somehow develop all those skills, or many of those skills? Can you become a multitalented tester?

Yes, you can. By understanding the combination of needed skills for different testing tasks, you can develop your own personal career path to become a true multitalent. Not only test automation, not only usability testing, not only being a scrum master, but, for example, a combination of all of them.

The presentation will outline typical backgrounds for testers, different skills, different learning routes, and different typical combinations of multitalents.

Kari will also briefly share his route to becoming the Tester of the Year 2021 after a 25-year journey, his own multitalentedness. It is then up to you to see which one is for you, or do you want to become your own, unique testing multitalent?

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