BDD: When Outcomes don't Come Out
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BDD is largely a goal-driven approach: we start from a context and explore whether some particular event will lead to the outcome we want. So how does it work when the outcomes are unclear, or you're just trying to find out what's possible? When finding examples changes the examples, is it possible to automate?
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BDD: When Outcomes don't Come Out
Elizabeth Keogh
Liz Keogh is a Lean and Agile consultant based in London. She is a well-known blogger and international speaker, a core member of the BDD community and a contributor to a number of open-source projects including JBehave. She specializes in helping people use examples and stories to communicate, build, test and deliver value, particularly when faced with high risk and uncertainty. Liz's work covers topics as diverse as story-writing, haiku poetry, Cynefin and complexity thinking, effective personal feedback and OO development, and she has a particular love of people, language, and choices. She has a strong technical background with over 15 years’ experience in delivering value and coaching others to deliver, from small start-ups to global enterprises. Most of her work now focuses on Lean, Agile and organizational transformations, and the use of transparency, positive language, well-formed outcomes and safe-to-fail experiments in making change innovative, easy and fun.