Mutation Testing
Mutation testing is over 50 years old, but hardly anyone uses it. How mutants help to find test gaps and write better code.
Mutation testing is over 50 years old, but hardly anyone uses it. How mutants help to find test gaps and write better code.
25 to 30 test design techniques exist, but most testers hardly use any of them. Why five of them are enough for 90% of all testing tasks.
Why does your brain just not understand some code? Working memory only processes four chunks at a time, and good code respects this limit.
700.000 lines of code in a combi steamer, 2,000 test cases per night: how test automation really works in device development.
Who is really responsible for quality in a company often remains unclear. The ACT2LEAD model shows what leadership in testing actually looks like.
Why do some teams feel great after shared work - and others wear down? What separates smart organizations from dumb ones.
AI is becoming the standard tool in testing, accessibility is becoming mandatory and test automation continues to gain momentum. What really matters in 2025.
AI dominates programming and testing, but lags behind in requirements engineering. Where Scrum really stands today and what that means for software quality.
Accessibility does not work automatically just because components are accessible. What goes wrong when assembling and why manual testing remains.
What happens when a third of the adopted code is only available as a black box? How an agile mindset and honesty can save a ticket store project.
Anyone familiar with impostor syndrome knows that rational thinking often doesn't help. Which strategies really lead out of the impostor cycle.
Model-based testing sounds good, but often fails due to a gap between the abstract model and the actual test. Why this is the case and how a two-phase approach can help.
AI-generated test code that compiles but tests the wrong thing: Why writing unit testers yourself and having business code generated instead is often the smarter approach.
Testing proves bugs, but never freedom from bugs. Formal methods can do this, from type systems to verified kernels, and the effort is more scalable than expected.
What does quality actually mean when no one in the team has an answer? A look back at 20 years of testing and the questions that are now becoming urgent.
Why do testing activities always end in a traffic jam just before go-live? Shift left alone is not enough: How synthetic monitoring reuses the same test case.
Production data often only covers 70% of test cases. How to systematically test data processes and get business and IT on the same page.
More data does not automatically mean better decisions. Which software metrics really help and why context is more important than any number.