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Ask Me Anything about AI, Test Automation and Skills - Richard Seidl

Written by Richard Seidl | Jul 17, 2024 10:00:00 PM

In this special summer episode, I’ve answered some of the most frequently asked questions you’ve sent me over the last few months. For example, what trends to keep an eye on, what the most common mistakes are in software testing in companies and what skills testers will need in the future.

“If there’s a problem that I can solve with AI, then let’s do it. Just installing something now and it only creates more work - that’s no good at all.” - Richard Seidl

Richie is an expert in software quality and agility and a passionate optimist about the future. As a consultant, coach and mentor, he supports companies on their way to more quality in software. For him, one thing is clear: if you want to create excellent software today, you need to think about the development process holistically: people, context, methods and tools - a mindset for developing potential and innovation only emerges when everything works together.

Highlights of this Episode:

  • Trends in software testing: testing AI and using AI, test data management, holistic quality and regulatory requirements.
  • Missing test strategies and the importance of good test cases in companies.
  • The role of static analysis and quick wins in the software testing process.
  • Important skills for software testers: teamwork, soft skills and technical knowledge.
  • The importance of communication and collaboration in an agile environment.
  • A personal story about the successful transformation of a team in the financial sector.
  • Insight into my daily work and what I particularly enjoy about it.
  • Information on mastermind groups and their benefits for professional development.
  • Call for articles for the German Testing Magazine and contributions for the German Testing Day.

In this episode of ‘Software Testing’, host Richie answers listeners’ questions about current trends and challenges in software testing. We talk about the importance of AI, test data management and the need for a holistic approach to quality in agile teams.

One of the most exciting developments in software testing is undoubtedly artificial intelligence (AI). Laura asked me what trends testers should definitely keep an eye on. There are two main aspects here: firstly, how do we test AI ourselves? And secondly, how can AI support us in testing? AI testing is still a very young field. However, there are already helpful resources such as the book “Basiswissen KI-Testen” by Röttger and Runze. A basic understanding of what quality means in AI is essential. There is also the question of the practical benefits of AI for our daily testing tasks - be it through automated test cases or tools such as Copilot.

Test data management: an unresolved challenge

In addition to AI, the management of test data is another key issue. Many companies struggle to find efficient solutions for test data. Yet the topic is becoming increasingly important due to regulatory requirements. Good test data management is essential for successful tests and future developments. I am therefore convinced that specialists in this area will be in high demand in the coming years.

Holistic view of quality

Another point that I often observe is the need for a holistic approach to quality. The days when developers and testers could work strictly separately are over. In agile teams in particular, we need to think about quality in a more integrated way. This also includes integrating non-functional tests such as penetration tests or usability tests into the design at an early stage. This comprehensive approach not only helps to avoid mountains of technical debt, but also contributes to the long-term development of maintainable and high-quality software.

Common errors in software testing

Michael wanted to know what common mistakes I see companies making when it comes to software testing. One of the biggest mistakes is the lack of a clear testing strategy. Without such a strategy, there is usually no risk-based approach to identifying the necessary tests and methods. The quality of existing tests also often leaves a lot to be desired. Although many projects have numerous automated tests, their effectiveness is limited. Static analysis tools are a no-brainer here in order to identify and reduce technical debt at an early stage.

Important skills for testers of the future

Yvonne asked about the skills and knowledge that testers need for the future. In addition to sound technical knowledge, soft skills have become essential. The ability to communicate transparently and work together in a team plays a decisive role in the success of a project. Agility means not only flexible processes, but above all cooperative work within the team. Testers should therefore increasingly see themselves as an integral part of the entire development process.

Personal experiences from everyday working life

Finally, I would like to share a personal experience: I was particularly touched by the story of a finance team. Initially, the team consisted of isolated developers and a single tester - a typical constellation with many difficulties. However, through continuous retrospectives and joint work, the team developed into a cooperative unit. The highlight was a morning of pair testing between developer and tester - a moment that showed how important communication and collaboration really are.