• views: 75
• date: 16 January 2026
• posted by: voska89

For Developers, Programmers and Engineers to learn how to translate Stories and Examples into Executable Specifications; build durable tests and Automated Test infrastructure; and use Acceptance Tests to write prompts and improve AI-generated code.
What's In This Course?
Learn how to specify ideas for new software and features in ways that are more understandable.
Replace expensive manual testing with high-level, automated Acceptance Testing that is stable and resilient to changes to the system or environment.
Dave Farley shares his expertise, and demonstrates techniques from complex projects (widely seen as world-class examples) of the practices to write "Acceptance Tests" in the form of "Executable Specifications".
And Now - "Acceptance Testing as Programming Language for AI". Learn how well-written Acceptance Tests, using a DSL approach, can significantly improve AI-generated code.
Why Acceptance Test? and What tools and techniques are effective?
How to avoid tests that are difficult, fragile, slow and prone to intermittent failure
Capturing & Translating Requirements
Scope & Properties of Good Acceptance Tests
Practical Exercises in Writing Specifications and Story-Mapping
Managing Test Isolation, Intermittency and Asynchrony
Using Acceptance Testing as a precise language to write prompts
How to verify the AI-generated code with Acceptance Tests
Test Strategy; how to build effective, efficient test cases in complex systems
Learn from the Expert
Dave Farley, one of the pioneers of Acceptance Testing, shares his Expertise, Teachings and Advice with YOU in Video Lessons, Worksheets and Demos, to Study at Your Convenience.
For Less Than 40% of the Price (compared to Dave's in-person training events).
Course Objectives
* Learn tools and techniques to analyse problems in a way that helps to determine which product features to develop.
* Practise effective story-writing using a combination of "Story Mapping" and "Specification by Example" techniques.
* Know how to create and use a "Domain Specific Language" to support the creation and maintenance of "Executable Specifications".
*Build Acceptance Tests, as Executable Specifications, that are not compromised by changes in the system under test.
*Learn how to build effective, efficient test cases in complex systems.
*Understand how well-written Acceptance Tests, using a DSL approach, can significantly improve AI-generated code.
Homepage
https://courses.cd.training/courses/atdd-from-stories-to-executable-specifications






   
   
   

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