This thesis aims at empowering software customers with a tool to build software tests them selves, based on a gradual refinement of natural language scenarios into executable visual test models. The process is divided in five steps:
1. First, a natural language parser is used to extract a graph of grammatical relations from the textual scenario descriptions.
2. The resulting graph is transformed into an informal story pattern by interpreting structurization rules based on Fujaba Story Diagrams.
3. While the informal story pattern can already be used by humans the diagram still lacks technical details, especially type information. To add them, a recommender based framework uses web sites and other resources to generate formalization rules.
4. As a preparation for the code generation the classes derived for formal story patterns are aligned across all story steps, substituting a class diagram.
5. Finally, a headless version of Fujaba is used to generate an executable JUnit test.
This result paves the way for online collaboration between global teams of software customers, IT business analysts and software developers.