Hardware-in-the-Loop Testing: Kernels on Real CPUs
A kernel has to run on every CPU generation, so hardware-in-the-loop testing puts it on real devices. Developers and CI reserve clean machines.
Podcast Software Testing
300+ episodes episodes with testers, developers, and coaches. Sometimes technical, sometimes uncomfortable. One question runs through all of them: what do you actually need to know, now that machines handle the obvious?
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Conversations with testers, developers, and coaches who work in the field.
Mutation Coverage: Why Green Tests Can Still Be Worthless
Mutation coverage measures how many deliberately planted bugs your tests catch. It says more than code coverage, especially when AI agents write tests.
How to Build Rules and Skills So That Agents Can Remember
AI coding agents need fewer manual reviews once you work on the system itself: rules, hooks and retro skills make their corrections stick for good.
AI-Generated Code: Quality Assurance Must Keep Pace
More AI-generated code means more defects, and only about 30% of AI review comments help. Static analysis, test selection and reviews must scale too.
ISTQB Boards in DACH: One Back Office for All Three
The ISTQB boards of Germany, Austria and Switzerland share one back office, which has kept their volunteer work running for up to 20 years.
Quality Sprint: How a Workshop Solves Quality Problems
A Quality Sprint tackles persistent quality issues in one workshop day with all stakeholders, ending in three to four next steps with clear owners.
Branch Coverage: Full Coverage Still Lets Bugs Through
Even 100% branch coverage let an off-by-one bug slip through. Coverage is only as good as its assertions, and loops need several iterations.
LLM Testing: A Second Model Acts as the Judge
LLM testing can be automated if you accept non-determinism: rubrics and acceptance ranges replace yes/no asserts, and a calibrated LLM judges outputs.
Resilience in Software Projects: Follow the Bug Trend
Resilience in software projects starts with accepting bugs rather than avoiding them. What bacteria and moths teach about trends and testing hypotheses.
Vibecoding and the Lack of System Understanding in Practice
Vibe coding risks grow where system understanding is missing. The future belongs to Pi-shaped developers who combine breadth with real depth.
Diversity in Software Teams: More Perspectives in the Product
Diversity in software teams matters: homogeneous teams build products that reflect only one perspective. Design, psychology and sociology fill the gaps.
QA Training for Autistic Adults: ISTQB in Four Weeks
QA training for autistic adults works with clear instructions, time boxes and a fixed contact. Repetitive regression tests play to autistic strengths.
Automatically Reviewing Documentation with AI Personas
Documentation testing with AI personas: a simulated junior developer burned 1.8 million tokens where a senior needed 300,000, exposing gaps in the docs.
Architecture Fitness Functions: Making Decisions Testable
Architecture fitness functions turn design decisions into testable KPIs, so hard-to-reverse Type 1 decisions defend themselves against violations.
Positive Leadership: How PERMA Links Well-Being and Results
Positive leadership ties appreciation to measurable results. The PERMA model names five evidence-based strategies for well-being and performance.
What AI Really Does to Trust and Team Dynamics
Heavy AI use erodes trust in teams: colleagues seem infallible, and friction and social learning fade. Strong teams onboard AI like a new team member.
Barriers to Innovation: How Processes Paralyze Corporations
Barriers to innovation in German corporations start with excessive processes. AI won't pay off either while nobody cleans up decades-old data silos.
Generative AI Ethics: The Case Against Hyperscale Models
Generative AI cannot be used ethically as long as training data is used without consent and billionaires control the models.