AI can make mistakes, so automated testing of AI-generated code is essential. Ultimately, you need to know
whether the program does what it is supposed to do. AI can help create tests, but developers still need to
understand, review and maintain them. In this practical workshop, you learn the fundamentals of automated
testing and how to use AI effectively without blindly trusting its results.
Through guided exercises, you read, write and improve unit tests yourself and with AI assistance. You learn to
provide useful context, identify missing scenarios and edge cases, and review assertions and test results. We
use TDD as a teaching method to introduce unit testing, not as a required workflow for everyday development.
You also explore integration tests, the purposeful use of mocks and stubs, and Testcontainers with Docker for
tests against real dependencies. Practical exercises show how to investigate failures and maintain reliable
tests.
Alternating theory, hands-on exercises and gamification make testing accessible and engaging.
Learn:
How to read, write and maintain unit tests, from Arrange-Act-Assert to test data and edge
cases
How to use integration tests, mocks and stubs appropriately and test real dependencies with
Testcontainers and Docker
How to generate and improve tests with AI using meaningful context and prompts
How to review AI-generated tests critically, find missing scenarios and investigate failures
How to build reliable, maintainable tests through guided exercises and gamification
How to read, write and maintain unit tests, from Arrange-Act-Assert to test data and edge
cases
How to use integration tests, mocks and stubs appropriately and test real dependencies with
Testcontainers and Docker
How to generate and improve tests with AI using meaningful context and prompts
How to review AI-generated tests critically, find missing scenarios and investigate failures
How to build reliable, maintainable tests through guided exercises and gamification
References
Workshop
minimum 4 participants.
Content
Show details
Normal
2 Days
2d
Introduction
1st Minute: 1st Test
Definition Automated Test
Reasons for Testing
Debts
✓
✓ ✓ ✓ ✓
Basic Unit Testing
How Unit Tests work
Tripple A Pattern (AAA)
Rules for clean tests
Exercise
✓
✓ ✓ ✓ ✓
Advanced Unit Testing
Contract Testing
Advanced Annotations
Setup (BeforeEach, BeforeAll)
DisplayName
Disabled Tests (and when to do it)
Package Protected Tests
Teardown (AfterEach, AfterAll)
Test Data (ValueSource, MethodSource, Theory, ...)
Testing Exceptions
Exercise
Test Data - Edge Cases
Test Data - Error Values
Test Data - Equivalence Classes
Test Data - Combinatorics
Test Data - Randomized
Exercise
✓
✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
Testing with AI
Providing requirements, context and effective prompts
Generating and improving tests with AI
Reviewing assertions, test cases and missing edge cases
Investigating failures and correcting flawed tests
Limitations, human responsibility and handling sensitive code
Hands-on exercises with an AI coding assistant
✓
✓ ✓ ✓ ✓ ✓ ✓
Integration tests and dependencies
Choosing between unit and integration tests
Purposeful use of mocks and stubs
Reducing dependencies with the Integration Operation Segregation Principle (IOSP)
Testing real dependencies with Testcontainers and Docker
Reliable test setup, isolation and cleanup
Practical integration testing exercise
✓
✓ ✓ ✓ ✓ ✓ ✓
Certificate
✓
per participant, plus VAT and traveling cost according to expenditure
My experience with the Clean Code training (2 days) was great. I gained a lot of knowledge about
clean code, refactoring, unit tests and various software design techniques. The trainer conveyed
the information in a very engaging way. There was always an opportunity to ask questions. I can
definitely recommend the Clean Code training for junior developers.
Henning
We have now completed our third training with Stefan Dirschnabel and it was once again a great
benefit for our team. Preparation top-notch, very structured process and excellent expertise. All
questions were answered and we were also offered help going forward. Thank you Stefan for the
training. We will definitely come back!
Johannes
Would do it again anytime! The Clean Code training was very well structured, had an enormous
amount of content, and was also wonderfully varied and entertaining. You can tell that Stefan
Dirschnabel brings not only a great deal of knowledge and experience, but also great enthusiasm
for software development!
You ask, we answer
What do participants need to bring?
Each participant needs a computer and familiarity with their development environment and a programming language. For the exercises, participants need access to an AI coding assistant and must be able to install and run the required software, including Docker.
How high is the practical portion of the training?
Very high. The workshop alternates short theory sections with guided exercises in which participants read, write, review and improve tests, both independently and with AI assistance.
Can the training be booked remotely?
Yes, the training can also be conducted remotely. However, since the course is very practice-oriented, we recommend an in-house delivery to optimally ensure individual attention and direct interaction with participants.
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